The improved entropy weighting model in water quality evaluation based on the compound function

被引:0
|
作者
Luo Xi
Zeng Qin
Yan Feng
机构
[1] Hohai University,College of Water Conservancy and Hydropower Engineering
[2] Nanchang University,Key Laboratory of Poyang Lake Environment and Resource Utilization, Ministry of Education
[3] Nanchang University,School of Civil Engineering and Architecture
来源
Environmental Monitoring and Assessment | 2022年 / 194卷
关键词
Entropy weight model; Dispersion degree; Pollution degree; Water quality evaluation; Poyang Lake; Compound function;
D O I
暂无
中图分类号
学科分类号
摘要
Entropy weight model (EWM) is widely used in water quality evaluation. In the conventional EWM, the weight is a monotone increasing function of the dispersion degree. However, this weighting principle often neglects the heavily polluted indicators. To solve this problem, an improved EWM is designed, in which the weight of the indicator is a compound function of its dispersion degree and pollution degree. In the clean domain, the weight increases with the dispersion degree, while in the polluted domain, the weight decreases with the dispersion degree. And for the same dispersion degree, the larger the pollution degree is, the higher the weight is, and vice versa. Subsequently, the improved EWM is applied to the water quality evaluation of Wucheng Wetland in Poyang Lake, China. Results are as follows: (i) For TP, CODMn, and NH3-N, their dispersion degrees are 0.001, 0.158, and 0.084; and their pollution degrees are 0.971, 0.277, and 0.281, respectively. (ii) According to the improved EWM, the weights of TP, CODMn, and NH3-N are 0.613, 0.197, and 0.190, respectively. (iii) The comprehensive water quality indices of estuary region, wetland region, and the central lake area are 32.5, 30.9, and 35.6, respectively, all of which belong to a “bad” grade. The water environment of Wucheng Wetland suffered serious damage of phosphorus, and the ecosystem faced a high threat. (iv) Compared with the conventional EWM, the improved EWM highlights the importance of polluted indicators, which makes the comprehensive evaluation results more rigorous and reasonable.
引用
收藏
相关论文
共 50 条
  • [1] The improved entropy weighting model in water quality evaluation based on the compound function
    Xi, Luo
    Qin, Zeng
    Feng, Yan
    ENVIRONMENTAL MONITORING AND ASSESSMENT, 2022, 194 (09)
  • [2] The pollution scale weighting model in water quality evaluation based on the improved fuzzy variable theory
    Zeng, Qin
    Luo, Xi
    Yan, Feng
    ECOLOGICAL INDICATORS, 2022, 135
  • [3] A Water Quality Evaluation Algorithm Based on Factor Weighting Model
    Man, Tantan
    Tan, Huobin
    Zhang, Kebing
    PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON ELECTRICAL & ELECTRONICS ENGINEERING AND COMPUTER SCIENCE (ICEEECS 2016), 2016, 50 : 370 - 373
  • [4] An improved approach for water quality evaluation: TOPSIS-based informative weighting and ranking (TIWR) approach
    Li, Zhenya
    Yang, Tao
    Huang, Ching-Sheng
    Xu, Chong-Yu
    Shao, Quanxi
    Shi, Pengfei
    Wang, Xiaoyan
    Cui, Tong
    ECOLOGICAL INDICATORS, 2018, 89 : 356 - 364
  • [5] Application of Improved Entropy-Weight TOPSIS Model Based on Gray Correlation Method (EWTG) to River Outfall Water Quality Evaluation
    Yuan, Hui
    Xu, Yuan
    Han, Shaoqiang
    Sun, Meng
    Ma, Nan
    Hao, Zhang
    Liu, Mao Hui
    2022 ASIA CONFERENCE ON ALGORITHMS, COMPUTING AND MACHINE LEARNING (CACML 2022), 2022, : 159 - 165
  • [6] WATER QUALITY EVALUATION OF YANHE RIVER BASED ON THE IMPROVED WATER POLLUTION INDEX
    Li, Ranran
    Zou, Zhihong
    An, Yan
    ICIM2014: PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON INDUSTRIAL MANAGEMENT, 2014, : 275 - 278
  • [7] Water Quality Evaluation and Prediction Based on a Combined Model
    Jiao, Guimei
    Chen, Shaokang
    Wang, Fei
    Wang, Zhaoyang
    Wang, Fanjuan
    Li, Hao
    Zhang, Fangjie
    Cai, Jiali
    Jin, Jing
    APPLIED SCIENCES-BASEL, 2023, 13 (03):
  • [8] An evaluation method for water quality based on the improved SOM neural network
    Li, Hongyi
    Li, Zexi
    Wang, Chaojie
    Han, Yuanfeng
    Zhao, Di
    He, Jingcheng
    MECHATRONICS, ROBOTICS AND AUTOMATION, PTS 1-3, 2013, 373-375 : 1220 - +
  • [9] Application of TOPSIS Model based on Vague Set Entropy in the Evaluation of Groundwater Quality
    Yu, Wenzhong
    Tang, Deshan
    ADVANCES IN MANUFACTURING SCIENCE AND ENGINEERING, PTS 1-4, 2013, 712-715 : 452 - 456
  • [10] An Evaluation Method of Water Quality Based on Improved PSO-BP Network
    Liu, Zuojun
    Li, Lihong
    ADVANCES IN MECHATRONICS, AUTOMATION AND APPLIED INFORMATION TECHNOLOGIES, PTS 1 AND 2, 2014, 846-847 : 1243 - +