International Journal of Research Studies in Science, Engineering and Technology Volume 5, Issue 2, 2018, PP 4-13 ISSN : 2349-476X Multivariate and Cluster Analysis of Hydrologic Indices: A Case Study of Karun Watershed, Khuzestan Province, Iran Elham Karimian1, Reza Modares1, Saeid Soltani1, Saeid Eslamian2, Kaveh Ostad-Ali-Askari3*, Vijay P. Singh4, Nicolas R. Dalezios5 1Department of Natural Resources Engineering, Isfahan University of Technology, Isfahan, Iran. 2Department of Water Engineering, Isfahan University of Technology, Isfahan, Iran. 3*Department of Civil Engineering, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran. (Corresponding Author) 4Department of Biological and Agricultural Engineering & Zachry Department of Civil Engineering, Texas A and M University, 321 Scoates Hall, 2117 TAMU, College Station, Texas 77843-2117, U.S.A. 5Laboratory of Hydrology, Department of Civil Engineering, University of Thessaly, Volos, Greece & Department of Natural Resources Development and Agricultural Engineering, Agricultural University of Athens, Athens, Greece. *Corresponding Author: Dr. Kaveh Ostad-Ali-Askari, Department of Civil Engineering, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran. Email:
[email protected] ABSTRACT Hydrological droughts usually affect large areas and minimum river flow is an appropriate index for the study of hydrological droughts. are commonly used for analyzing multivariate data? This study considered 35 hydrological indicators which were divided into 5 groups, including amplitude, duration, frequency, timing, variability, that characterized the various flow regime characteristics. Factor analysis and principal component analysis were used to calculate the hydrological indices for 14 stations of Karun watershed, Iran, and analyze the main components (PCAs). Then, the main components, the most important parameters of the Karun domain, which included A2, A4, D3, D5, V1, F and T, were determined and based on these indices, they were grouped by cluster analysis.