Technical Note Recognition of Homogeneous Regions Using K-means Partitional Cluster Analysis Method Based on Second-order L-moment (Case Study: Roodbar Dam and Bakhtiari Dam Basins)

Document Type : Original Article

Authors

1 M.Sc. of River Engineering, Shahid Abbaspour Campus, ShahidBeheshti University

2 M.Sc. of Agricultural Engineering – Water Structures, School of Agricultural Engineering, Shahrood University of Technology, Shahrood

3 Assistant Professor, Faculty of Water and Environmental Engineering, Shahid Abbaspour Campus, Shahid Beheshti University, تهران

4 Assistant Professor, Faculty of Water and Environmental Engineering, Shahid Abbaspour Campus, Shahid Beheshti University, Tehran

Abstract

A group of sites with sufficient homogeneity in producing flood mechanisms form a homogeneous region for regional flood frequency analysis. Cluster analysis is the generic name of a variety of multivariate statistical procedures that are used to classify given data into similar groups or clusters. This procedure is an efficient method for regional flood frequency analysis. In this article, cluster analysis of annual maximum flow data of 34 gauging stations located in Lorestan province in Roodbar Dam and Bakhtiari Dam basins for 2 to 6 clusters has been performed using R programming language. K-means algorithm that is a type of partitional clustering has been used for cluster analysis. Merged groups of sites have been formed and homogeneous groups of Roodbar and Bakhtiari dam basins has then been identified by performing homogeneity test.

Keywords

References

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شرکت توسعه منابع آب و نیروی ایران (b1385) گزارش هیدرولوژی طرح سد و نیروگاه برقابی رودبار.
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Iran-Water Resources Research
Volume 10, Issue 3 - Serial Number 3
February 2015
Pages 99-103

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History

  • Receive Date: 03 May 2013
  • Accept Date: 04 November 2014

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