Literature DB >> 28034435

Water quality assessment in Qu River based on fuzzy water pollution index method.

Ranran Li1, Zhihong Zou2, Yan An3.   

Abstract

A fuzzy improved water pollution index was proposed based on fuzzy inference system and water pollution index. This method can not only give a comprehensive water quality rank, but also describe the water quality situation with a quantitative value, which is convenient for the water quality comparison between the same ranks. This proposed method is used to assess water quality of Qu River in Sichuan, China. Data used in the assessment were collected from four monitoring stations from 2006 to 2010. The assessment results show that Qu River water quality presents a downward trend and the overall water quality in 2010 is the worst. The spatial variation indicates that water quality of Nanbashequ section is the pessimal. For the sake of comparison, fuzzy comprehensive evaluation and grey relational method were also employed to assess water quality of Qu River. The comparisons of these three approaches' assessment results show that the proposed method is reliable.
Copyright © 2016. Published by Elsevier B.V.

Entities:  

Keywords:  Fuzzy comprehensive evaluation; Fuzzy inference; Water pollution index; Water quality assessment

Mesh:

Year:  2016        PMID: 28034435     DOI: 10.1016/j.jes.2016.03.030

Source DB:  PubMed          Journal:  J Environ Sci (China)        ISSN: 1001-0742            Impact factor:   5.565


  4 in total

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3.  Heavy metal contamination in the complete stretch of Yamuna river: A fuzzy logic approach for comprehensive health risk assessment.

Authors:  Maneesh Jaiswal; Sanjay Kumar Gupta; Mayuri Chabukdhara; Mahmoud Nasr; Arvind Kumar Nema; Jakir Hussain; Tabarak Malik
Journal:  PLoS One       Date:  2022-08-08       Impact factor: 3.752

4.  Evaluation of water quality based on a machine learning algorithm and water quality index for the Ebinur Lake Watershed, China.

Authors:  Xiaoping Wang; Fei Zhang; Jianli Ding
Journal:  Sci Rep       Date:  2017-10-09       Impact factor: 4.379

  4 in total

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