Survey of water resources of Shiramin plain using multivariate statistical methods

Document Type : Complete scientific research article

Authors

1 Tabriz University

2 Ph.D student

Abstract

Background and Objectives: Groundwater is considered as one of the most important sources of fresh water which is available of human. Groundwater is used for various goals such as drinking, sanitation, agriculture and industry. Therefore Studying, understanding and protecting it looks a necessary work in arid and semi-arid areas like Iran. Shiramin region with an aquifer with approximate area of 34 km2 is one the marginal plains of Urmia lake. Deep understanding of the dominant hydrogeochemical processes on aquifer system is very important in the management of groundwater resources. Graphics methods are among the usual methods in the recognition of the dominant processes on the groundwater, but lack of use of some chemical parameters such as (nitrate, arsenic, etc.), including its limitations. Multivariate statistical analysis methods (Factor analysis, Clustering analysis) has been used as a complementary method along with graphics method to identify factors affecting the quality of underground water, finding the source of contamination and to classifying the similar samples. Using Geographic Information System (GIS) along with mentioned methods leading to better insight and easier understanding in groundwater issues. The aim of this study is to identify the effective factors on the quality of water resources of Shiramin region, finding their sources, and hydrogeochemical analysis of them using multivariate statistical analysis, graphical and GIS methods.
Materials and Methods: In order to investigate groundwater of Shiramin area, 18 samples of groundwater from all over the plain with regard to the best distribution, were collected and analyzed. For interpretation and representing the data, multivariate statistical analysis (principal component analysis (PCA) and hierarchical cluster analysis (HCA)), correlation matrix, graphical and GIS methods were used.
Results: Content of nitrate is higher and fluoride is less than the standard value. Factor analysis resulted in the extraction of four factors: (first component: carbonate component, the second component: component of rain-fed and the third component: from sulfoflouride, the fourth component, nitrate component). Hierarchical cluster analysis has resulted in the extraction of two clusters named HCA1 (first cluster) and HCA2 (second cluster). Samples related to first cluster in the upstream of plain illustrate better quality and samples related to second cluster are located in the downstream of plain with higher EC and lower quality.
Conclusion: Using multivariate statistical analysis methods in identifying Effective factors on water quality and clustering them is very effective. Graphical methods and GIS are also effective for understanding the Hydrogeochemical processes.



yes, no, yes.

Keywords

References

1.Adepelumi, A.A., Ako, B., Ajayi, T., Afolabi, O., and Omotoso, E. 2009. Delineation of saltwater intrusion into the freshwater aquifer of LekkiPeninsula, Lagos, Nigeria. Environmental Geology. 56: 5. 927-933.
2.Anayah, F.M., and Almasri, M.N. 2009. Trends and occurrences of nitrate in the groundwater of the West Bank, Palestine. Applied Geography. 29: 4. 588-601.
3.Andre, L., Franceschi, M., Pouchan, P., and Atteia, O. 2005. Using geochemical data and modelling to enhance the understanding of groundwater flow in a regional deep aquifer, Aquitaine Basin, south-west of France. J. Hydrol. 305: 1. 40-62.
4.Apha, A. 1998. Wpcf. Standard methods for the examination of water and wastewater 20.
5.Asghari Moghaddam, A., Nadiri, A.A., and Fijani, E. 2007. Spatial prediction of fluoride concentration using artificial neural networks and geostatic models. J. Sci. Water Soil.
J. 19/1. 129-145. (In Persian)
6.Chebotarev, I. 1955. Metamorphism of natural waters in the crust of weathering-1. Geochimica et Cosmochimica Acta. 8: 1. 22-48.
7.Davis, J.C. 1986. Statistical and data analysis in geology, J. Wiley.
8.Durov, S. 1948. Natural waters and graphic representation of their composition. Dokl Akad Nauk SSSR.
9.Güler, C., Thyne, G.D., McCray, J.E., and Turner, K.A. 2002. Evaluation of graphical
and multivariate statistical methods for classification of water chemistry data. Hydrogeol. J. 10: 4. 455-474.
10.Helena, B., Pardo, R., Vega, M., Barrado, E., Fernandez, J.M., and Fernandez, L. 2000. Temporal evolution of groundwater composition in an alluvial aquifer (Pisuerga River, Spain) by principal component analysis. Water research. 34: 3. 807-816.
11.Hossain, G., Howladar, M.F., Nessa, L., Ahmed, S.S., and Quamruzzaman, C. 2010. Hydrochemistry and classification of groundwater resources of Ishwardi Municipal Area, Pabna District, Bangladesh. Geotechnical and Geological Engineering. 28: 671-9.
12.Hounslow, A. 1995. Water quality data: analysis and interpretation, CRC press.
 13.Kaiser, H.F. 1958. The varimax criterion for analytic rotation in factor analysis. Psychometrika. 23: 3. 187-200.
14.Kaiser, H.F. 1974. An index of factorial simplicity. Psychometrika. 39: 1. 31-36.
15.Love, D., Hallbauer, D., Amos, A., and Hranova, R. 2004. Factor analysis as a tool in groundwater quality management: two southern African case studies. Physics and Chemistry of the Earth, Parts A/B/C. 29: 15. 1135-1143.
16.McNeil, V.H., Cox, M.E., and Preda, M. 2005. Assessment of chemical water types and
their spatial variation using multi-stage cluster analysis, Queensland, Australia. J. Hydrol. 310: 1. 181-200.
17.Moghaddam, A.A., and Fijani, E. 2009. Hydrogeologic framework of the Maku area basalts, northwestern Iran. Hydrogeol. J. 17: 4. 949-959. (In Persian)
18.Nadiri, A.A., Moghaddam, A.A., Tsai, F.T., and Fijani, E. 2013. Hydrogeochemical analysis for Tasuj plain aquifer, Iran. J. Earth Syst. Sci. 122: 4. 1091-1105.
19.Noori, R., Sabahi, M.S., Karbassi, A., Baghvand, A., and Zadeh, H.T. 2010. Multivariate statistical analysis of surface water quality based on correlations and variations in the data set. Desalination. 260: 1. 129-136.
20.Oudouris, K., Panagopoulos, A., and Koumantakis, J. 2000. Multivariate statistical analysis in the assessment of hydrochemistry of the Northern Korinthia prefecture alluvial aquifer system (Peloponnese, Greece). Natural Resources Research. 9: 2. 135-146.
21.Piper, A.M. 1944. A graphic procedure in the geochemical interpretation of water-analyses. Transactions, American Geophysical Union. 25: 914-928.
22.Pourakbar, M., Mosaferi, M., Shaker Khatibi, M., and Moradi, A. 2014. Groundwater quality assessment from a hydrogeochemical viewpoint a case Study of Sarab County. Adviser engineer of project and investigations of water and wastewater. 26: 3. 116-126. (In Persian)
23.Prasanna, M.V., Chidambaram, S., Hameed, A.S., and Srinivasamoorthy, K. 2011. Hydrogeochemical analysis and evaluation of groundwater quality in the Gadilam river basin, Tamil Nadu, India. J. Earth Syst. Sci. 120: 1. 85-98.
24.Prasanna, M.V., Chidambaram, S., and Srinivasamoorthy, K. 2010. Statistical analysis of the hydrogeochemical evolution of groundwater in hard and sedimentary aquifers system of Gadilam river basin, South India. J. King Saud Univ. - Sci. 22: 3. 133-145.
25.Shahrabi, M. 1994. Report of geological map of Quadrilateral Urmia with scale 250000/1. Geological Survey and mining Exploration. (In Persian)
26.Shanmugam, P., and Ambujam, N. 2012. A hydrochemical and geological investigation on the Mambakkam mini watershed, Kancheepuram District, Tamil Nadu. Environmental monitoring and assessment. 184: 5. 3293-3306.
27.Singh, K.P., Malik, A., Mohan, D., and Sinha, S. 2004. Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of GomtiRiver (India)-a case study. Water Research. 38: 18. 3980-3992.
28.Singhal, B., and Gupta, R. 1999. Applied Hydrogeology of Fractured Rocks. Kluwer Academic Publishers, Dordrecht, the Netherlands.
29.Tabachnick, B.G., and Fidell, L.S. 2001. Using multivariate statistics.
30.Todd, D.K., and Mays, L.W. 2005. Groundwater Hydrology. Wiley, New Jersey.
31.Vega, M., Pardo, R., Barrado, E., and Debán, L. 1998. Assessment of seasonal and
polluting effects on the quality of river water by exploratory data analysis. Water research. 32: 12. 3581-3592.
Journal of Water and Soil Conservation
Volume 23, Issue 3
September 2016
Pages 289-302

Files

Share

How to cite

Statistics