Assessing Spring Water Quality Using Geostatistical Modelling in a Semi-Arin Region: Ain Larbi Northeastern (Algeria) | ||||
| Egyptian Journal of Aquatic Biology and Fisheries | ||||
| Article 77, Volume 28, Issue 6, November 2024, Page 1357-1373 PDF (716.54 K) | ||||
| DOI: 10.21608/ejabf.2024.396344 | ||||
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| Author | ||||
| Samia et al. | ||||
| Abstract | ||||
| The current investigation was carried out to assess spring water quality in Ain Larbi, South of Guelma, Algeria. Physico chemical analyses were implemented to examine twenty water samples, gathered between January and July of 2022. For the first time in this region, water was characterized using a geostatistical modeling, principal component analysis (PCA), and ion exchange index. As part of the first inventory of water points in this region, a number of 16 parameters were investigated. The principal component analysis (PCA) applied on the standardized parameters identify factors responsible for variations and mineral correlation. Based on this methodology, groundwater quality in Ain Larbi area is primarily affected by weathering, geochemical processes, and human activities. The geostatistical modelling was calculated for each station based on physicochemical parameters during the wet and dry seasons. The results emphasize how groundwater ion concentrations are impacted by hydrogeological regimes (wet and dry seasons) as well as interactions between water and rocks. The findings demonstrate that every water sample taken into account for this investigation comes from a karst source evidenced by the geological section realized in this area. Limestone dissolution was also one of the proposed causes of elevated bicarbonate concentrations in the northern part of the investigated area. In this work, we identified that the findings from kriging, ion exchange index, and PCA were nearly identical, with a geographical distribution that provides a map of parameter distribution in the studied areas. The results concluded that geostatistical approach was found to be the best method compared to others. These results create a comprehensive database for the research area's groundwater management. | ||||
| Keywords | ||||
| Ain Larbi springs; Geostatistical model; ACP; Ions exchange; Rock weathering | ||||
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