Analysis of multiple parameters pollution map based on land use map and using K-mean clustering technique in Qazvin aquifer

Document Type : Research Article

Authors

1 Assistant professor of Irrigation and drainage department, Aburaihan campus, university of Tehran

2 M.Sc. Graduate Civil Engineering

Abstract

One of the main approaches to control and prevent the aquifers from contamination is to identify the critical contaminated areas in relation to the water application. Most of the researchers considered only one type of contamination or one type of water application. In this research, using cluster analysis and water application, a multi-parameter groundwater quality classification map is developed. Three water quality parameters including arsenic, total suspended solids, and nitrate for three different applications including agricultural, industrial and drinking purposes are used to develop a classified contamination map for an aquifer in central Iran, Qazvin aquifer. The optimal number of clusters is five and it is determined using Davies-Bouldin Index. Based on the standard of World Health Organization for drinking water and considering the three selected quality parameters, the results show that the most suitable class of the aquifer, Class C1, with 22 percent of total area is mostly in northern areas of the aquifer with minimum human activity. In central areas with increase in industrial and agricultural activities, the lower classes, C4 and C5, with 35 percent of total area are appeared.

Keywords

Main Subjects


1-      Neshat A, Pradhan B, Javadi S. Risk assessment of groundwater pollution using monte carlo approach in an agriculture region: an example from Kerman plain, Iran. Computers, Environment and urban system. 2015; 50(1): 66-73.
2-      Al-adamat R.A.N, Foster I.D.L, Baban S.M.J. Groundwater vulnerability and risk mapping for the Basaltic aquifer of the Azraq basin of Jordan using GIS and Remote sensing and DRASTIC, Applied Geography. 2003; 23(4): 303-324.
3-      Samani S, Kalantari N, Rahimi, M.H. Evaluation of groundwater quality by Cluster analysis technique in Avan aquifer, Journal of Water resources engineering. 2011; 4: 75-85. [Persian].
4-      Aghdar H, Mohammadyari F. Assessment of groundwater quality using Cluster analysis method in Mehran and Dehloran aquifer. The first international conference on new achievements in Agriculture, natural resources and environmental sciences. 2014. [Persian].
5-      Ouyang Y, Jia Zh, Cui L. Estimating impacts of land use on groundwater quality using trilinear analysis. Environmental monitoring and assessment. 2014; 186(9): 5353-5362.
6-      Ghiasi N, Arabkhedri M, Ghafari A, Hatami H. Survey on the effect of some morphometric characteristics of basins on peak discharge with different return periods (Case study north Albors basins). Research and development journal. 2004; 62: 2-10. [Persian].
7-      Goulet V, Rocourt J, Jacquet C. Cluster of listeriosis cases in France. Euro surveillance weekly. 2002; 27(6).
8-      Kim K J, Ahn H. A recommender system using GA K-means clustering in an online shopping market. Expert Syst. Appl. 2008; 34 (2): 1200–1209.
9-      Usman N, Toriman M.E, Juahir H. Assessment of Groundwater Quality Using Multivariate Statistical Techniques in Terengganu. Science and Technology, 2014; 4(3): 42-49.
10-  Zou H, Zou Z, Wang X. An Enhanced K-Means Algorithm for Water Quality Analysis of the Haihe River in China. Int. J. Environ. Res. Public Health. 2015; 12: 1400-1413.
11-  Azhar S.C, Aris A.Z, Yussof M.K, Ramli M.F, Juahir H. Classification of river water quality using multivariate analysis. Procedia Environmental Sciences. 2015; 30: 79-84.
12-  Oorkavalan G, Chidambaram S.M, Mariappan V, Kandaswamy G, Natarajan S. Cluster Analysis to Assess Groundwater Quality in Erode District, Tamil Nadu, India. Circuits and Systems, 2016; 7: 877-890.
13-  Fianko J.R, Osae S, Adomako D, Achel D.J. Relationship between land use and groundwater quality in six districts in the eastern region of Ghana. Environmental Monitoring and Assessment. 2009; 153(4): 139-146.
14-  Yongjun J, Daoxian Y, Shiyou X, Linli L, Gui Zh, Raosheng H. Groundwater quality and land use change in a typical karst agricultural region: a case study of Xiaojiang watershed, Yunnan. Journal of geographical Sciences. 2006; 16(4): 405-414.
15-  Lerner D, Harris B. The relationship between land use and groundwater resources and quality. Land Use Policy. 2009; 26(1): 265-273.
16-  Announcement. Hydrogeology section- the report of Quality and Quantity Modelling study in Qazvin aquifer. Qazvin Regional Water Company. 2012: 23-26. [Persian].
17-  Han J, Kamber M. Data mining concepts and techniques. San Francisco, U.S.A, Morgan Kaufman Publisher. 2006: 110.
18-    Hoppner F, Klawonn F, Kruse R, Runkler T. Fuzzy cluster analysis. Sussex, England: Wiley and Sons. 1999: 146.
19-  Feil B. Fuzzy Clustering in Process of Data Mining. Ph.D. thesis, Department of Process Engineering, University of Veszprem Hungary. 2006.
20-  Kim D.W, Lee K.H, Lee D. On cluster validity index for estimation of the optimal number of fuzzy clusters. Journal of Pattern Recognition Society. 2004; 37: 209-225.
21-  Hashemy S.M. Spatial and Temporal Clustering in Irrigation network using classic and fuzzy technique. M.Sc. thesis, Tarbiat Modares University. 2008. [Persian].
22-  Davies D.L, Bouldin D.W. A cluster separation measure. IEEE Trans. Pattern Anal. Mach. Intell. 1979; 1(4): 224–227.
Volume 5, Issue 1
April 2018
Pages 293-305
  • Receive Date: 20 April 2017
  • Revise Date: 02 August 2017
  • Accept Date: 22 August 2017
  • First Publish Date: 21 March 2018
  • Publish Date: 21 March 2018