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Abstract
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Article Information:
Multivariate Statistical Analysis of Geochemical Data of Groundwater in El-Bahariya Oasis, Western Desert, Egypt
Ali M. Hamdan
Corresponding Author: Ali Hamdan
Submitted: April 20, 2012
Accepted: May 14, 2012
Published: June 30, 2012 |
Abstract:
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The aim of the present study is to study the application of multivariate statistical analyses of
hydrochemical data using the chemical analyses for 125 groundwater samples with 18 parameters include the
hyrdrochemical compositions (Ca2+, Mg2+, Na+, K+, (HCO3), (SO4)2− and Cl−) and the physicochemical
parameters (EC, TDS, TH, SAR, RSBC, PI, KR, SSP, MAR, RSC and Na%). The linear regression is an
approach to modeling the relationship between two variables using a set of individual data point and used to
explain or predict the behavior of a dependent variable. Two variables were used to develop a relationship
between TDS as an independent variable and different hyrdrochemical data as a dependent variable. Using these
equations, by known TDS value, the equation tries to predict any unknown other variables. The linear
regression equations used also between the EC as an independent variable and all different water quality
variables. The correlation matrix performed for the groundwater using the hyrdrochemical compositions (r
varies from 0.84 to 0.08). All data have positive relations reflecting direct relationship with all hydrochemical
data. Good correlation observed between TDS and each of other variables, while weak positive relation detected
between (HCO3) and Ca2+, (SO4)2−, Ng2+ and Cl−. Two clusters were performed, the first use TDS, Ca, Mg, Na,
K, HCO3, SO4, Cl, EC and TH while the second use PI, TH, MAR, EC, SAR, KR, Na%, RSBC, RSC and SSP
as variables. Skewness and kurtosis are calculated for all data to describe the shape and symmetry of the
distribution of geochemical data along the study area. Skewness values vary from 3.22 to -1.36. Positive
skewness were notice in most parameters indicates that the shape of their statistical distribution diagrams show
the tail on the right side (direction of high values) is longer than the left side and the bulk of the values (possibly
including the median) lie to the left of the mean for each parameter. Kurtosis values vary from 18.17 (for SO4)
to -0.65 (for RSBC). Positive Kurtosis characterize most parameters indicates a peaked distribution relative to
a normal distribution of the data, while the other are negative (indicates a flat distribution). The SO4, KR, MAR
and TH have high kurtosis values, indicates tend to have a distinct peak near the mean and have heavy tails.
Key words: Cluster analysis , Egypt, El-bahariya oasis, hydrochemistry, kewness and kurtosis, statistical analysis, western desert
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Cite this Reference:
Ali M. Hamdan, . Multivariate Statistical Analysis of Geochemical Data of Groundwater in El-Bahariya Oasis, Western Desert, Egypt. Research Journal of Environmental and Earth Sciences, (06): 665-667.
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ISSN (Online): 2041-0492
ISSN (Print): 2041-0484 |
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