alexa Principle Component Analysis of Longitudinal Dispersion Coefficient Parameters
E-ISSN: 2252-5211

International Journal of Waste Resources
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Research Article

Principle Component Analysis of Longitudinal Dispersion Coefficient Parameters

Abbas Parsaie* and Amir Hamzeh Haghiabi

Department of water Engineering, Lorestan University, Khorram Abad, Iran

*Corresponding Author:
Abbas Parsaie, Ph.D
Candidate of Hydro Structures
Department of Water Engineering
Lorestan University, Khorram Abad, Iran
Tel: +989163685867

Received date October 10, 2015; Accepted date November 12, 2015; Published date November 19, 2015

Citation: Parsaie A, Haghiabi AH (2015) Principle Component Analysis of Longitudinal Dispersion Coefficient Parameters . J Waste Resources 5:186. doi: 10.4172/2252-5211.1000186

Copyright: © 2015 Parsaie A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



Study on the river water quality is a main part of environmental engineering. Longitudinal dispersion coefficient ( DL ) is one of the main important parameters in the river water quality studies. Several parameters such as hydraulically and morphological rivers are affective on the DL , whereas the mount effectiveness of some of them such as riverbed form cannot be measured. So, researchers proposed that the DL is proportional to the flow velocity, channel width, river flow depth, and shear velocity. Defining the most influence parameters on the DL leads to develop an optimal structure for empirical formulas and soft computing techniques which will be propose for estimation of DL .In this paper the principle component analysis (PCA) was used to define the most affective parameters on the DL . The PCA results indicated that the width of the river, flow depth, and flow velocity are the most important parameters on the DL . Evaluating the performance of empirical formulas with considering the PCA results showed that the Tavakollizadeh and Kashefipur formula is accurate among the empirical formulas.


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