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TRAORE ADIARATOU, Xumei Mao, Alhousseyni Traore, YAHAYA YAKUBU, Aboubacar Sidibe. Multivariate statistical analysis of dominating groundwater mineralization and hydrochemical evolution in Gao, northern Mali. Journal of Earth Science. doi: 10.1007/s12583-022-1689-y
Citation: TRAORE ADIARATOU, Xumei Mao, Alhousseyni Traore, YAHAYA YAKUBU, Aboubacar Sidibe. Multivariate statistical analysis of dominating groundwater mineralization and hydrochemical evolution in Gao, northern Mali. Journal of Earth Science. doi: 10.1007/s12583-022-1689-y

Multivariate statistical analysis of dominating groundwater mineralization and hydrochemical evolution in Gao, northern Mali

doi: 10.1007/s12583-022-1689-y
  • Received Date: 05 Dec 2021
  • Rev Recd Date: 27 May 2022
  • Accepted Date: 31 May 2022
  • Available Online: 23 Jul 2022
  • Population growth and expanding urbanization have caused persistent shortages and contamination of groundwater resources in Mali, Africa. The increase in groundwater salinity makes it more difficult for residents to obtain drinking water, it is necessary to clarify the causes and control factors of groundwater mineralization in Gao region, northern Mali. Based on the analysis of the hydrochemical composition of groundwater in 24 boreholes, Piper and Schöeller diagrams, principal component analysis (PCA) and hierarchical cluster analysis (HCA) are used to carry out multivariate statistical analysis on the main ions. The results show that the groundwater samples are weakly alkaline, with pH values ranging from 5.83 to 8.40, and the average values of boreholes are 7.50, respectively. The average electrical conductivity (EC) value is 354.4 (µS/cm), and the extreme value is between 124.0 and 1247 (µS/cm). Water is usually mineralized and presents nine types of water phase. The three principal components explain 84.42% of the total variance for 13 parameters. The factor F1 (58.85%), the factor F2 (16.88%) and the factor F3 (8.69%) present for the majority of the total data set. In addition, multivariate statistical analysis confirmed the genetic relationship among aquifers and identified three main clusters. Clustering related to groundwater mineralization (F1), clustering related to oxide reduction and iron enrichment (F2), and clustering of groundwater pollution caused by nitrate and magnesium (F3). We found that agriculture, weathering activities and dissolution of geological materials promote the mineralization of groundwater. Groundwater quality in the Gao region is becoming less and less potable because of increasing salinity.

     

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