• ISSN 2305-7068
  • Indexed by ESCI CABI CAS
  • DOAJ Scopus GeoRef AJ CNKI
Advanced Search
Volume 8 Issue 3
Sep.  2020
Turn off MathJax
Article Contents
Mehdi Bahrami, Elmira Khaksar, Elahe Khaksar. 2020: Spatial variation assessment of groundwater quality using multivariate statistical analysis(Case Study: Fasa Plain, Iran). Journal of Groundwater Science and Engineering, 8(3): 230-243. doi: 10.19637/j.cnki.2305-7068.2020.03.004
Citation: Mehdi Bahrami, Elmira Khaksar, Elahe Khaksar. 2020: Spatial variation assessment of groundwater quality using multivariate statistical analysis(Case Study: Fasa Plain, Iran). Journal of Groundwater Science and Engineering, 8(3): 230-243. doi: 10.19637/j.cnki.2305-7068.2020.03.004

Spatial variation assessment of groundwater quality using multivariate statistical analysis(Case Study: Fasa Plain, Iran)

doi: 10.19637/j.cnki.2305-7068.2020.03.004
More Information
  • Corresponding author: Mehdi Bahrami, E-mail: bahrami@fasau.ac.ir
  • Received Date: 2019-12-16
  • Accepted Date: 2020-03-22
  • Publish Date: 2020-09-28
  • Groundwater is considered as one of the most important sources for water supply in Iran. The Fasa Plain in Fars Province, Southern Iran is one of the major areas of wheat production using groundwater for irrigation. A large population also uses local groundwater for drinking purposes. Therefore, in this study, this plain was selected to assess the spatial variability of groundwater quality and also to identify main parameters affecting the water quality using multivariate statistical techniques such as Cluster Analysis (CA), Discriminant Analysis (DA), and Principal Component Analysis (PCA). Water quality data was monitored at 22 different wells, for five years (2009-2014) with 10 water quality parameters. By using cluster analysis, the sampling wells were grouped into two clusters with distinct water qualities at different locations. The Lasso Discriminant Analysis (LDA) technique was used to assess the spatial variability of water quality. Based on the results, all of the variables except sodium absorption ratio (SAR) are effective in the LDA model with all variables affording 92.80% correct assignation to discriminate between the clusters from the primary 10 variables. Principal component (PC) analysis and factor analysis reduced the complex data matrix into two main components, accounting for more than 95.93% of the total variance. The first PC contained the parameters of TH, Ca2+, and Mg2+. Therefore, the first dominant factor was hardness. In the second PC, Cl-, SAR, and Na+ were the dominant parameters, which may indicate salinity. The originally acquired factors illustrate natural (existence of geological formations) and anthropogenic (improper disposal of domestic and agricultural wastes) factors which affect the groundwater quality.
  • 加载中
  • Alavi M. 2004. Regional stratigraphy of the Zagros fold-thrust belt of Iran and its pro-foreland evolution. American Journal of Science, 304: 1-20. doi:  10.2475/ajs.304.1.1
    Amiri MJ, Bahrami M, Beigzadeh B, et al. 2018. A response surface methodology for optimization of 2, 4-dichlorophenoxyacetic acid removal from synthetic and drainage water: A comparative study. Environmental Science and Pollution Research, 25(34): 34277-34293. doi:  10.1007/s11356-018-3327-x
    Azhar SC, Aris AZ, Yusoff MK, et al. 2015. Classification of river water quality using multivariate analysis. Procedia Environmental Sciences, 30: 79-84. doi:  10.1016/j.proenv.2015.10.014
    Bagheri R, Bagheri F, Eggenkamp HGM. 2017. Origin of groundwater salinity in the Fasa Plain, southern Iran, hydrogeochemical and isotopic approaches. Environmental Earth Sciences, 76: 662. doi:  10.1007/s12665-017-6998-6
    Bahrami M, Amiri MJ, Beigzadeh B. 2018. Adsorption of 2, 4-dichlorophenoxyacetic acid using rice husk biochar, granular activated carbon, and multi-walled carbon nanotubes in a fixed bed column system. Water Science and Technology, 78(8): 1812-1821. doi:  10.2166/wst.2018.467
    Bahrami M, Brumand-Nasab S, Kashkooli HA, et al. 2013. Cadmium removal from aqueous solutions using modified magnetite nanoparticles. Iranian Journal of Health and Environment, 6(2): 221-232. http://www.researchgate.net/publication/313403189_Cadmium_removal_from_aqueous_solutions_using_modified_magnetite_nanoparticles
    Bahrami M, Zarei AR, Chakav S. 2017. Analysis of drought transitions using log-linear models in Iran. International Journal of Water, 11(3): 266-278. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=53a548b314951d9d6fa4ebe78702fb2a
    Bencer S, Boudoukha A, Mouni L. 2016. Multivariate statistical analysis of the ground-water of Ain Djacer area (Eastern of Algeria). Arabian Journal of Geosciences, 9(4): 1-10. doi:  10.1007/s12517-015-2277-6
    Dehghani R, Mahvi AH, Rabani D, et al. 2015. Evaluation of chemical quality and salinity origin of groundwater in a semi aried area; Seyed Gholi region Saveh, Iran. Archives of Hygiene Sciences, 4(2): 100-108. http://jhygiene.muq.ac.ir/article-1-142-en.html
    Ebrahimzadeh S, Boustani F, Shakeri A. 2011. Groundwater quality assessment of the Zarghan Plain, Shiraz, Iran. 2nd International Conference on Environmental Science and Technology IPCBEE, 6. Singapore: IACSIT Press.
    El Alfy M, Faraj T. 2016. Spatial distribution and health risk assessment for groundwater contamination from intensive pesticide use in arid areas. Environmental Geochemistry and Health, 39: 231-253. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=a1c0d801ff212841c8abbf755852ea01
    El Alfy M, Lashin A, Abdalla F, et al. 2017. Assessing the hydrogeochemical processes affecting groundwater pollution in arid areas using an integration of geochemical equilibrium and multivariate statistical techniques. Environmental Pollution, 229: 760-770. doi:  10.1016/j.envpol.2017.05.052
    Freeze RA, Cherry JA. 1979. Groundwater. Newjersey: Prentice-Hall, inc: 604.
    Ghassemi Dehnavi A. 2018. Hydrochemical assessment of groundwater using statistical methods and ionic ratios in Aliguodarz, Lorestan, west of Iran. Journal of Advances in Environmental Health Research, 6: 193-201. http://cn.bing.com/academic/profile?id=66059a58629cb5afd206a8f45101e331&encoded=0&v=paper_preview&mkt=zh-cn
    Hardle W, Simar L. 2007. Applied multivariate statistical analysis, 2nd edn. Berlin: Springer.
    Helena B, Pardo R, Vega M, et al. 2000. Temporal evolution of groundwater composition in an alluvial aquifer (Pisuerga River, Spain) by principal component analysis. Water Research, 34(3): 807-816. http://www.cabdirect.org/abstracts/20001907737.html
    Hummel M, Edelmann D, Kopp-Schneider A. 2017. Clustering of samples and variables with mixed-type data. PLOS ONE, 12(11):e0188274. https://doi.org/10.1371/journal.pone.0188274 doi:  10.1371/journal.pone.0188274
    Institute of Standards and Industrial Research of Iran. 2009. Drinking water-physical and chemical specifications. ISIRI No. 1053, the 5th Revision. http://www.isiri.org/Portal/Home/Default.aspx?CategoryID=5f6bbf1b-ac23-4362-a309-9ee95a439628
    Lokhande PB, Patil VV, Mujawar HA. 2008. Multivariate statistical analysis of ground-water in the vicinity of Mahad industrial area of Konkan Region, India. International Journal of Applied Environmental Sciences, 3(2): 149-163. http://www.highbeam.com/doc/1G1-216041380.html
    Mahmood A, Muqbool W, Mumtaz MW, et al. 2011. Application of multivariate statistical techniques for the characterization of groundwater quality of Lahore, Gujranwala and Sialkot (Pakistan). Pakistan Journal of Analytical & Environmental Chemistry, 12(1): 102-112. http://www.oalib.com/paper/2093766
    Matiatos I, Alexopoulos A, Godelitsas A. 2014. Multivariate statistical analysis of the hydrogeochemical and isotopic composition of the groundwater resources in northeastern Peloponnesus (Greece). Science of the Total Environment: 476-477, 577-590. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dccb7a7f1a26b0a4426d481f6e8ccabb
    Matiatos I. 2016. Nitrate source identification in groundwater of multiple land-use areas by combining isotopes and multivariate statistical analysis: A case study of Asopos basin (Central Greece). Science of the Total Environment, 541: 802-814. doi:  10.1016/j.scitotenv.2015.09.134
    Matiatos I, Evelpidou N. 2013. Assessment of groundwater quality contamination by nitrate leaching using multivariate statistics and Geographic Information Systems. Understanding freshwater quality problems in a changing world, 361: 183-190. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=CC0214089213
    Matiatos I, Paraskevopoulou V, Botsou F, et al. 2016. Hydrogeochemical assessment of groundwater quality in a river delta using multivariate statistical techniques. EGU General Assembly Conference Abstracts, 18: 14568. http://adsabs.harvard.edu/doi/2016EGUGA..1814568M
    McKenna Jr JE. 2003. An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis. Environmental Modelling and Software, 18(3): 205-220. doi:  10.1016/S1364-8152(02)00094-4
    Mozafarizadeh J, Sajadi Z. 2013. Investigation of saline water intrusion in the Borazjan freshwater aquifer from the Dalaki and Helleh rivers. Journal of Electromagnetic and Application, 6(16): 69-78. http://openurl.ebscohost.com/linksvc/linking.aspx?stitle=Journal%20of%20Electromagnetic%20Waves%20and%20Applications&volume=27&issue=18&spage=2298
    Noshadi M, Ghafourian A. 2016. Groundwater quality analysis using multivariate statistical techniques (Case study: Fars Province, Iran). Environmental Monitoring and Assessment, 188: 1-13. doi:  10.1007/s10661-015-4999-z
    Nosrati K, Van Den Eeckhaut M. 2012. Assessment of groundwater quality using multivariate statistical techniques in the Hashtgerd Plain, Iran. Environmental Earth Sciences, 65(1): 331-344. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=4e5c8d7399179d583e4877b20172da8f
    Pandit S, Gupta S. 2011. A comparative study on distance measuring approaches for clustering. International Journal of Computer Science, 2(1): 29-31. http://www.oalib.com/paper/2758894
    Rogerson PA. 2001. Statistical methods for geography. London: Sage Publications Ltd.
    Sarbu C, Pop HF. 2005. Principal component analysis versus fuzzy principal component analysis. A case study: The quality of Danube water (1985-1996). Talanta, 65: 1215-1220. http://cn.bing.com/academic/profile?id=b77299b2e3cdaae5fa7f659261ff8787&encoded=0&v=paper_preview&mkt=zh-cn
    Singh KP, Malik A, Sinha S. 2005. Water quality assessment and apportionment of pollution sources of Gomti River (India) using multivariate statistical techniques: A case study. Analytica Chimica Acta, 538(1-2): 355-374. doi:  10.1016/j.aca.2005.02.006
    Singh A, Yadav A, Rana A. 2013. K-means with three different distance metrics. International Journal of Computer Applications, 67(10): 13-17. doi:  10.5120/11430-6785
    Srivastava SK, Ramanathan AL. 2008. Geo-chemical assessment of groundwater quality in vicinity of Bhalswa landfill, Delhi, India, using graphical and multivariate statistical methods. Environmental Geology (Berlin), 53: 1509-1528. doi:  10.1007/s00254-007-0762-2
    US Salinity Laboratory Staff. 1954. Diagnosis and improvement of saline and alkali soils. Washington DC: US Department of Agriculture Handbook, 60: 160.
    Usman UN, Toriman ME, Juahir H, et al. 2014. Assessment of groundwater quality using multivariate statistical techniques in Terengganu. Science and Technology, 4(3):42-49. DOI:  10.5923/j.scit.20140403.02
    Witten DM, Tibshirani R. 2011. Penalized classification using Fisher's linear discriminant. Journal of the Royal Statistical Society, 73(5): 753-772. doi:  10.1111/j.1467-9868.2011.00783.x
    Yidana SM. 2010. Groundwater classification using multivariate statistical methods: Birimian Basin, Ghana. Journal of Environmental Engineering, 136(12): 1379-1388. doi:  10.1061/(ASCE)EE.1943-7870.0000291
    Zarei AR, Bahrami M. 2016. Evaluation of quality and quantity changes of undergroundwater in the Fasa Plain, Fars (2006-2013). Iranian Journal of Irrigation & Water Engineering, 6(24): 103-113. http://www.researchgate.net/publication/309291575_Evaluation_of_quality_and_quantity_changes_of_underground_water_in_Fasa_plain_Fars_2006_-_2013
  • Relative Articles

    [1] Masoud H Hamed, Rebwar N Dara, Marios C Kirlas, 2024: Groundwater vulnerability assessment using a GIS-based DRASTIC method in the Erbil Dumpsite area (Kani Qirzhala), Central Erbil Basin, North Iraq, Journal of Groundwater Science and Engineering, 12, 16-33.  doi: 10.26599/JGSE.2024.9280003
    [2] Vinay Kumar Gautam, Mahesh Kothari, P.K. Singh, S.R. Bhakar, K.K. Yadav, 2022: Analysis of groundwater level trend in Jakham River Basin of Southern Rajasthan, Journal of Groundwater Science and Engineering, 10, 1-9.  doi: 10.19637/j.cnki.2305-7068.2022.01.001
    [3] KHELFAOUI Hakim, DAJBRI Larbi, LAKHAL Fatima Zohra, CHAFFAI Hicham, HANI Azzedine, SAYAD Lamine, 2020: Determination of the origin of mineralization and groundwater salinity in the Adrar region in the southwest of Algeria, Journal of Groundwater Science and Engineering, 8, 158-171.  doi: 10.19637/j.cnki.2305-7068.2020.02.007
    [4] Abdelhakim LAHJOUJ, Abdellah EL HMAIDI, Karima BOUHAFA, 2020: Spatial and statistical assessment of nitrate contamination in groundwater: Case of Sais Basin, Morocco, Journal of Groundwater Science and Engineering, 8, 143-157.  doi: 10.19637/j.cnki.2305-7068.2020.02.006
    [5] Negar Fathi, Mohammad Bagher Rahnama, Mohammad Zounemat Kermani, 2020: Spatial analysis of groundwater quality for drinking purpose in Sirjan Plain, Iran by fuzzy logic in GIS, Journal of Groundwater Science and Engineering, 8, 67-78.  doi: 10.19637/j.cnki.2305-7068.2020.01.007
    [6] Prusty Rabiranjan, Biswal Trinath, 2020: Physico-chemical, bacteriological and health hazard effect analysis of the water in Taladanda Canal, Paradip area, Odisha, India, Journal of Groundwater Science and Engineering, 8, 338-348.  doi: 10.19637/j.cnki.2305-7068.2020.04.004
    [7] LI Yang, KANG Feng-Xin, ZOU An-de, 2019: Isotope analysis of nitrate pollution sources in groundwater of Dong’e geohydrological unit, Journal of Groundwater Science and Engineering, 7, 145-154.  doi: 10.19637/j.cnki.2305-7068.2019.02.005
    [8] LI Xiao-hang, WANG Rui, LI Jian-feng, 2018: Study on hydrochemical characteristics and formation mechanism of shallow groundwater in eastern Songnen Plain, Journal of Groundwater Science and Engineering, 6, 161-170.  doi: 10.19637/j.cnki.2305-7068.2018.03.001
    [9] Eunhee Lee, Kyoochul Ha, Nguyen Thi Minh Ngoc, Adichat Surinkum, Ramasamy Jayakumar, Yongje Kim, Kamaludin Bin Hassan, 2017: Groundwater status and associated issues in the Mekong-Lancang River Basin: International collaborations to achieve sustainable groundwater resources, Journal of Groundwater Science and Engineering, 5, 1-13.
    [10] Khongsab Somphone, OunakoneKone Xayviliya, 2017: Climate change and groundwater resources in Lao PDR, Journal of Groundwater Science and Engineering, 5, 53-58.
    [11] BAI Bing, CHENG Yan-pei, JIANG Zhong-cheng, ZHANG Cheng, 2017: Climate change and groundwater resources in China, Journal of Groundwater Science and Engineering, 5, 44-52.
    [12] Chamroeun SOK, Sokuntheara CHOUP, 2017: Climate change and groundwater resources in Cambodia, Journal of Groundwater Science and Engineering, 5, 31-43.
    [13] Pezhman ROUDGARMI, Ebrahim FARAHANI, 2017: Investigation of groundwater quantitative change, Tehran Province, Iran, Journal of Groundwater Science and Engineering, 5, 278-285.
    [14] YU Kai-ning, LI Jian, LI Hui, CHEN Kang, LV Bing-xu, ZHAO Long-hui, 2016: Statistical characteristics of heavy metals content in groundwater and their interrelationships in a certain antimony mine area, Journal of Groundwater Science and Engineering, 4, 284-292.
    [15] ZHANG Chun-chao, WANG Wen-Ke, SUN Yi-bo, LI Xiang-quan,HOU Xin-wei, 2015: Processes of hydrogeochemical evolution of groundwater in the Guanzhong Basin, China, Journal of Groundwater Science and Engineering, 3, 136-146.
    [16] Liang ZHU, Wei-dong KANG, Ji-chao SUN, Jing-tao LIU, 2014: Quantitative Calculation of Groundwater Vulnerability Assessment Based on Quantification Theory III, Journal of Groundwater Science and Engineering, 2, 78-85.
    [17] MA Shao-bing, ZHOU Jun, LIANG Peng, SU Yao-ming, 2014: Characteristics-based classification research on typical petroleum contaminants of groundwater, Journal of Groundwater Science and Engineering, 2, 41-47.
    [18] Jingli Shao, Yali Cui, Yunzhang Zhao, 2013: A Study on Infiltration and Groundwater Development in the Influent Zone of the Perched Lower Yellow River, Journal of Groundwater Science and Engineering, 1, 46-53.
    [19] Jiansheng Shi, Hongtao Liu, Zhiyuan Liu, Tieliu Chen, 2013: Application of the “Accurate Control Groundwater Resources” Theory in Containment of Groundwater Resource Exhaustion Trend, Journal of Groundwater Science and Engineering, 1, 1-10.
    [20] Song Bo, Liu Changli, Zhang Yun, Hou Hongbing, Pei Lixin, Yang Liu, 2013: Urban Waste Disposal and Its Impact on Groundwater Pollution in China, Journal of Groundwater Science and Engineering, 1, 88-95.
  • 加载中

Catalog

    Figures(6)  / Tables(10)

    Article Metrics

    Article views (1072) PDF downloads(109) Cited by()
    Proportional views
    Related

    Welcome to Journal of Groundwater Science and  Engineering!

    Quick Submit

    Online Submission   E-mail Submission

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return