Groundwater quality assessment using multivariate analysis, geostatistical modeling, and water quali

• 作者: Oualid Bouteraa Azeddine Mebarki Foued Bouaicha Zeineddine Nouaceur Benoit Laignel
• 学科: 地球科学
• 关键词: Groundwater Multivariate analysis Geostatistical modeling Geochemical modeling Mineralization Ordinary Kriging
• 年，卷（期）: 2022,（6）
• 页码范围: 796-814
• 页数: 18页
• 语种: 英文
• DOI: 10.1007/s11631-019-00329-x

摘要

In this study, the analytical data set of 26 groundwater samples from the alluvial aquifer of Boumerzoug-El khroub valley has been processed simultaneously with Multivariate analysis, geostatistical modeling, WQI, and geochemical modeling. Cluster analysis identified three main water types based on the major ion contents, where mineralization increased from group 1 to group 3. These groups were confirmed by FA/PCA, which demonstrated that groundwater quality is influenced by geochemical processes (water–rock interaction) and human practice (irrigation). The exponential semivariogram model fitted best for all hydrochemical parameters values and WQI. Groundwater chemistry has a strong spatial structure for Mg, Na, Cl, and NO3, and a moderate spatial structure for EC, Ca, K, HCO3, and SO4. Water quality maps generated using ordinary Kriging are consistent with the HCA and PCA results. All water groups are supersaturated with respect to carbonate minerals, and dissolution of kaolinite and Ca-smectite is one of the processes responsible for hydrochemical evolution in the area.