Robustness of fuzzy c-mean method for delineation of hydrochemical facies distribution of groundwater in Varamin Plain
Subject Areas :
Mohammad
Nakhaei
1
Mehdi
Talkhabi
2
Meysam
Vadiati
3
Keywords: Groundwater Hydrochemical Facies Clustering Fuzzy Logic Varamin.,
Abstract :
In this paper, classification of a large hydrochemical data set from Varamin plain is done by using fuzzy c-means (FCM) and hierarchical cluster analysis (HCA) clustering techniques. Then its application to hydrochemical facies delineation is discussed. Groundwater samples were grouped into three classes according to the optimum number of the classes and fuzziness exponent by using the fuzzy c-mean. The data set includes 90 deep and moderate deep well samples from groundwater data set and 9 hydrochemical variables were used. Results from both FCM and HCA clustering produced cluster centers that can be used to identify the physical and chemical processes creating the variations in the water chemistries. The optimum cluster in FCM method determined by optimization function, but in HCA method by trial and error. The FCM method is potentially useful in establishing hydrochemical facies distribution and may provide a better tool than HCA for clustering large data sets when overlapping or continuous clusters exist. Plotting the cluster membership value contours on a map demonstrated the existence of three spatially continuous, well-defined clusters of groundwater samples. The results showed that the FCM method is more sound for investigating threshold data rather than HCA method (that represents sharp and abrupt variations).
آذر، ع. و فرجي، ح.، 1386. علم مديريت فازي. انتشارات موسسه كتاب مهربان نشر.
آقانباتي، ع.، ۱۳۸۵. زمين‌شناسي ايران. انتشارات سازمان زمين‌شناسي و اکتشافات معدني کشور.
تشنه‌لب، م.، صفارپور، ن. و افيوني، د.، 1387. سيستم‌هاي فازي و کنترل فازي. انتشارات دانشگاه صنعتي خواجه‌نصيرالدين طوسي.
سازمان زمین شناسی کشور، 1385. نقشه زمين¬شناسي یک صدهزارم ورامین، سازمان زمين¬شناسي و اكتشافات معدني کشور.
سلطاني محمدي، س.، علي نيا، ف. و آوياني، د.، ۱۳۸۶. خنثي‌سازي اثر سنژنتيک داده‌هاي ژئوشيميايي رسوبات آبراهه‌اي در منطقه شمال تکاب با استفاده از خوشه‌بندي فازي. اميرکبير، ۶۷، ۲۷-۳۴.
شكاري، پ. و باقر نژاد، م.، ۱۳۸۴. بررسي کاربرد روش فازي در طبقه‌بندي خاک، مطالعه موردي: چشمه سفيد کرمانشاه. علوم و فنون کشاورزي و منابع طبيعي زمستان، ۹، ۵۵-۶۸.
طاهري، م.، 1378. آشنايي با نظريه مجموعه‌هاي فازي. انتشارات جهاد دانشگاهي مشهد.
کوره‌پزان دزفولي، ا.، 1387. اصول تئوري مجموعه‌هاي فازي و کاربرد آن در مدل‌سازي مسائل مهندسي آب. انتشارات جهاد دانشگاهي واحد صنعتي امير کبير.
Alimohammadlou, Y., Najafi, A. and Gokceoglu, C., 2014. Estimation of rainfall-induced landslides using ANN and fuzzy clustering methods: A case study in Saeen Slope, Azerbaijan province, Iran. Catena, 120, 149-162.
Ay, M. and Kisi, O., 2014. Modelling of chemical oxygen demand by using ANNs, ANFIS and k means clustering techniques Journal of Hydrology, 511, 279–289.
Barbieri, P., Adami, G., Favretto, A., Lutman, A., Avoscan, W. and Reisenhofer, E., 2001. Robust cluster analysis for detecting physicochemical typologies of freshwater from wells of the plain of Friuli (northeastern Italy). Analytica Chimica Acta, 440, 161–170.
Bezdek, J.C., 1981. Pattern Recognition with Fuzzy Objective Function Algorithms Plenum, 256.
Burrough, P.A., Van Gaans, P.M. and McMillan, R.A., 2000. High resolution landform classification using fuzzy k-means. Fuzzy Sets Systems, 113, 37-52.
Goyal, M.K. and Gupta, V., 2014. Identification of Homogeneous Rainfall Regimes in Northeast Region of India using Fuzzy Cluster Analysis. Water Resources Management, 28, 4491-4511.
Guler, C. and Thyne, G.D., 2004. Delineation of hydrochemical facies distribution in a regional groundwater system by means of fuzzy c-means clustering. Water Resource Research, 40, w12503. Doi: 10.1029/2004WR003299.
Guler, C., Thyne, G.D., McCray, J.E. and Turner, A.K., 2002. Evaluation of graphical and multivariate statistical methods for classification of water chemistry data. Hydrogeology Journal, 10, 455– 474.
Hathaway, R.J. and Bezdek, J.C., 2001. Fuzzy C-means clustering of incomplete data. IEEE Transactions System Man and Cybernetics, 31, 735– 744.
McBratney, A.B. and Moore, A.W., 1985. Application of fuzzy sets to climatic classification. Agriculture and Forest Meteorology, 35, 165– 185.
Rantitsch, G., 2000. Application of fuzzy clusters to quantify lithological background concentrations in stream-sediment geochemistry. Journal of Geochemical Exploration, 71, 73– 82.
Singh, K., Malik, A., Mohan, D. and Sinha, S., 2004. Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)-a case study. Water Research, 38, 3980-3992.
Todd, K.D., and Mays, 2005. Groundwater Hydrology. John Wiley and Sons. 636. Zadeh, L.A., 1965. Fuzzy sets. Information Control, 8, 338– 353.
Zhang, C.T., Chou, K.C. and Maggiora, G.M., 1995. Predicting protein structural classes from amino acid composition: Application of fuzzy clustering. Protein Engineering, 8, 425–435.