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Using Multivariate Statistical Analysis, Geostatistical Techniques and Structural Equation Modeling to Identify Spatial Variability of Groundwater Quality

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  • Lazhar Belkhiri
  • Tahoora Narany

Abstract

Multivariate statistical analysis, geostatistical techniques and structural equation modeling were used to determine the main factors and mechanisms controlling the spatial variation of groundwater quality in the Ain Azel plain, Algeria. Cluster analysis grouped the sampling wells into two statistically significant clusters based on similarities of groundwater quality characteristics. Principal component and factor analyses (PCA/ FA) revealed that two factors explained around 85 % of the total variance, which water-rock interaction and anthropogenic impact as the dominant factors affecting the groundwater quality. The distribution of factor score one represents high loading for EC, Ca, Mg, Na, K, and SO 4 in the western side and south eastern side of the plain, where water-rock interactions are dominate factors influence groundwater quality. Spatial distribution map of factor score 2 indicate that NO 3 , NO 2 , NH 4 , and COD show high concentration in central and southern side of the plain, where anthropogenic impact reduce groundwater quality. Further, one-way analysis of variance (one-way ANOVA) showed that the mean differences between cluster one and two show significantly differences for some water quality parameters including EC, Ca, Mg, Na, K, Cl, and SO 4 . Structural equation modeling (SEM) confirmed the finding of multivariate analysis. This study provides a new technique of confirming exploratory data analysis using SEM in groundwater quality. Copyright Springer Science+Business Media Dordrecht 2015

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  • Lazhar Belkhiri & Tahoora Narany, 2015. "Using Multivariate Statistical Analysis, Geostatistical Techniques and Structural Equation Modeling to Identify Spatial Variability of Groundwater Quality," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 2073-2089, April.
  • Handle: RePEc:spr:waterr:v:29:y:2015:i:6:p:2073-2089
    DOI: 10.1007/s11269-015-0929-7
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    2. Can Bülent Karakuş, 2020. "Evaluation of water quality of Kızılırmak River (Sivas/Turkey) using geo-statistical and multivariable statistical approaches," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(5), pages 4735-4769, June.
    3. Ali Athamena & Aissam Gaagai & Hani Amir Aouissi & Juris Burlakovs & Selma Bencedira & Ivar Zekker & Andrey E. Krauklis, 2022. "Chemometrics of the Environment: Hydrochemical Characterization of Groundwater in Lioua Plain (North Africa) Using Time Series and Multivariate Statistical Analysis," Sustainability, MDPI, vol. 15(1), pages 1-28, December.
    4. Mohamed Alfy & Aref Lashin & Nassir Al-Arifi & Abdulaziz Al-Bassam, 2015. "Groundwater Characteristics and Pollution Assessment Using Integrated Hydrochemical Investigations GIS and Multivariate Geostatistical Techniques in Arid Areas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5593-5612, December.
    5. Mohamed Abd El-Wahed & Mohamed M. El-Horiny & Mahmoud Ashmawy & Samar Abd El Kereem, 2022. "Multivariate Statistical Analysis and Structural Sovereignty for Geochemical Assessment and Groundwater Prevalence in Bahariya Oasis, Western Desert, Egypt," Sustainability, MDPI, vol. 14(12), pages 1-27, June.
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    7. Aliasghar Azma & Esmaeil Narreie & Abouzar Shojaaddini & Nima Kianfar & Ramin Kiyanfar & Seyed Mehdi Seyed Alizadeh & Afshin Davarpanah, 2021. "Statistical Modeling for Spatial Groundwater Potential Map Based on GIS Technique," Sustainability, MDPI, vol. 13(7), pages 1-18, March.
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