University of Tehran Press Journal of Ecohydrology 2423-6098 4 3 2017 09 23 Definition of Sarab Aquifer Hydrochemical Facies Distribution by means of Fuzzy C-Mean Clustering and Hierarchical Cluster Analysis Methods Definition of Sarab Aquifer Hydrochemical Facies Distribution by means of Fuzzy C-Mean Clustering and Hierarchical Cluster Analysis Methods 763 773 62624 10.22059/ije.2017.62624 FA Meisam Vadiati PhD Student, Faculty of Natural Science, University of Tabriz, Tabriz Asghar Asghari Moghaddam Professor, Faculty of Natural Science, University of Tabriz, Tabriz Muhammad Nakhaei Professor, Faculty of Earth Science, Kharazmi University, Tehran Journal Article 2017 01 20 In this research, clustering of a hydrochemical data set from Sarab plain aquifer has been carried out using Fuzzy C-Means (FCM) and Hierarchical Cluster Analysis (HCA) techniques and its application in delineation of hydrochemical facies has been studied. The statistical clusters analyze the spatial coherence indicating that that the clusters have a hydrogeological correspondence with aquifer hydrochemical facies. Groundwater samples were grouped into four classes using the fuzzy c-mean. The data set includes 49 water samples and 12 hydrochemical variables selected from the study area. The results obtained from both approaches presented cluster centers that can be used in order to identify the physical and chemical processes causing variations in the hydrochemistry variation of study area. The FCM method is potentially useful in establishing hydrochemical facies distribution. The results showed that the clustering scheme for partitioning water chemistry samples into homogeneous groups produced by FCM method is an important tool for determination of aquifer hydrochemical facies and the FCM method is more capable to investigate threshold data than HCA method which is characterized by sharp and abrupt variation. In this research, clustering of a hydrochemical data set from Sarab plain aquifer has been carried out using Fuzzy C-Means (FCM) and Hierarchical Cluster Analysis (HCA) techniques and its application in delineation of hydrochemical facies has been studied. The statistical clusters analyze the spatial coherence indicating that that the clusters have a hydrogeological correspondence with aquifer hydrochemical facies. Groundwater samples were grouped into four classes using the fuzzy c-mean. The data set includes 49 water samples and 12 hydrochemical variables selected from the study area. The results obtained from both approaches presented cluster centers that can be used in order to identify the physical and chemical processes causing variations in the hydrochemistry variation of study area. The FCM method is potentially useful in establishing hydrochemical facies distribution. The results showed that the clustering scheme for partitioning water chemistry samples into homogeneous groups produced by FCM method is an important tool for determination of aquifer hydrochemical facies and the FCM method is more capable to investigate threshold data than HCA method which is characterized by sharp and abrupt variation. https://ije.ut.ac.ir/article_62624_e3f0b56743a77aa47b404ebadf762674.pdf