Issue |
MATEC Web Conf.
Volume 246, 2018
2018 International Symposium on Water System Operations (ISWSO 2018)
|
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Article Number | 02004 | |
Number of page(s) | 5 | |
Section | Parallel Session I: Water Resources System | |
DOI | https://doi.org/10.1051/matecconf/201824602004 | |
Published online | 07 December 2018 |
Application of Grey Clustering Method Based on Improved Analytic Hierarchy Process in Water Quality Evaluation
1 State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China
2 State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
3 Xishan Coal Electricity Group Co., Ltd Taiyuan 030205, China
a Corresponding author: wangxu_04@126.com
To highlight the differences in water quality impacts of different indicators in water samples, this paper proposes a grey clustering method based on improved analytic hierarchy process to evaluate the quality of surface water. According to the pollution degree of different indicators in the water quality sample, the importance score is assigned, and the weight of different indicators is calculated by the analytic hierarchy process. The weight participates in the calculation of the grey clustering coefficient, and the evaluated water quality category considers the difference of the contribution rate of different pollutant indicators. The water quality samples of three water periods (Abundant, Normal, and Poor water flow periods) in the four sections of Qingshui River in Duyun City (Tea garden, Youhang, Yingpan and Jiadeng) were selected for evaluation, and the conventional grey clustering method and single factor method were used. The evaluation results were compared and analyzed. The evaluation results show that the improved grey clustering method is more scientific and reasonable and can provide a basis for water quality assessment and water environment management of water environment management departments.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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