scholarly journals Incorporating pollutants interaction with the environment and parameter uncertainty in water quality evaluation: a case of Lake Chauhan, China

2017 ◽  
Vol 18 (2) ◽  
pp. 723-736 ◽  
Author(s):  
Jingneng Ni ◽  
Jiuping Xu ◽  
Mengxiang Zhang
Keyword(s):  
Water Quality ◽  
Parameter Uncertainty ◽  
Water Resource Management ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Water Environment ◽  
Management Decision ◽  
Water Quality Evaluation ◽  
New Approach

Abstract Water quality evaluation is a key task in water resource management and pollution control. Current evaluation methods are rooted in water quality index, which assesses the water quality based on the exact concentration of various pollutants. However, the interaction between the pollutants and the water environment should also be considered. This paper suggests a new approach, which integrates pollutant interaction with water environment and parameter uncertainty to water quality evaluation. The new approach is compared with traditional methods. Then, an inexact evaluation model, the integrated water quality evaluation model under uncertainty, is established in accordance with the proposed approach, in which catastrophe theory is used to deal with the ambiguous internal mechanism of the interaction between the pollutants and the water environment. As there are significant uncertainties in water quality evaluations, fuzzy random variables are employed to describe the inexact monitoring data. To solve the proposed model, a new algorithm is designed. The model is then applied to an actual case: Lake Chaohu, China. The results are compared between the proposed method and China's current evaluation method (i.e. max-index method). Some brief analysis and discussion are given about the results, which could be helpful in guiding environmental management decision-making.

Improved Fuzzy Equilibrium Average Type Comprehensive Evaluation Method in the Application of Water Quality Evaluation

2013 ◽  
Vol 779-780 ◽  
pp. 1619-1622 ◽  
Author(s):  
Jun Pan ◽  
Bo Yao Li ◽  
Ming Cen Jiang
Keyword(s):  
Water Quality ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Evaluation Process ◽  
Fuzzy Comprehensive Evaluation ◽  
Water Quality Evaluation ◽  
Fuzzy Comprehensive Evaluation Method ◽  
Comprehensive Evaluation Method

In order to improve the traditional fuzzy comprehensive evaluation model of main factors, the paper used the shortage of the outstanding balance average type instead of traditional fuzzy comprehensive evaluation method in the evaluation process and takes big or small algorithm, this method to avoid maximum membership principle may cause information loss, more objective quantitative determination of water quality class. This paper Liaozhong waterfront city underground water quality testing data as the basis, an improved fuzzy comprehensive evaluation method to evaluate, the result is due to the area of iron and manganese from groundwater seriously overweight cause groundwater quality grade V. Show that the method of water quality evaluation, the result more objective and accurate.

scholarly journals Research on application of ReliefF and improved RVM in water quality grade evaluation

2022 ◽  
Author(s):  
Yu-Lin Gong ◽  
Ming-Jia Hu ◽  
Hui-Fang Yang ◽  
Bo Han
Keyword(s):  
Water Quality ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Threshold Value ◽  
Pso Algorithm ◽  
Relevance Vector Machine ◽  
Water Quality Evaluation ◽  
Quality Grade ◽  
Factor Combination ◽  
Research On Application

Abstract ReliefF algorithm was used to analyze the weight of each water quality evaluation factor, and then based on the Relevance Vector Machine (RVM), Particle Swarm Optimization (PSO) was used to optimize the kernel width factor and hyperparameters of RVM to build a water quality evaluation model, and the experimental results of RVM, PSO-RVM, ReliefF-RVM and PSO-ReliefF-RVM were compared. The results show that ReliefF algorithm, combined with threshold value, selects 5 evaluation factors with significant weight from 8 evaluation factors, which reduces the amount of data used in the model, CSI index is used to calculate the separability of each evaluation factor combination. The results show that the overall separability of the combination is best when the evaluation factor with significant weight is reserved. When different water quality evaluation factors were included, the evaluation accuracy of PSO-ReliefF-RVM model reached 95.74%, 14.23% higher than that of RVM model, which verified the effectiveness of PSO algorithm and ReliefF algorithm, and had a higher guiding significance for the study of water quality grade evaluation. It has good practical application value.

scholarly journals Hydrochemical Characteristics and Water Quality Evaluation of Rivers in Different Regions of Cities: A Case Study of Suzhou City in Northern Anhui Province, China

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 950 ◽  
Author(s):  
Yaqi Jiang ◽  
Herong Gui ◽  
Hao Yu ◽  
Meichen Wang ◽  
Hongxia Fang ◽  
...  
Keyword(s):  
Water Quality ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Class Iii ◽  
Hydrochemical Characteristics ◽  
Water Quality Evaluation ◽  
Hydrogen And Oxygen Isotope ◽  
The City

To study the disparity of river hydrochemical characteristics and water quality in different regions of the city, this paper took the Tuo River in the center of Suzhou, Northern Anhui, China and the Bian River on the edge of the urban area as the research objects, used Piper trigram, Gibbs diagram, and hydrogen and oxygen isotope content characteristics to analyze the geochemical characteristics of surface water in the study area, and then the improved fuzzy comprehensive evaluation method was used to evaluate the water quality. The results showed that the hydrochemical types of the two rivers were SO4-Cl-Na type, and the contents of Na+, K+, SO42−, Cl−, Ca2+, total phosphorus (TP) in the Bian River at the edge of the city were much higher than those in the Tuo River at the center of the city (ANOVA, p < 0.001). Gibbs diagram showed that the ion composition of the two rivers was mainly affected by rock weathering. The results of correlation analysis and water quality evaluation showed that Bian River was greatly affected by agricultural non-point source pollution, and its water quality was poor, class IV and class V water account for 95%, while, for Tuo River, due to the strong artificial protection, class II and class III accounted for 40.74% and 59.26%, respectively, and the overall water quality was better than that of Bian River. The evaluation results of irrigation water quality showed that the samples from Tuo River were high in salt and low in alkali, which could be used for irrigation when the soil leaching conditions were good, while Bian River water samples were high in salt and medium in alkali, which was suitable for irrigation of plants with strong salt tolerance.

scholarly journals Application of Set Pair Analysis Model Based on Interval Number in Water Quality Evaluation

2019 ◽  
Vol 7 (08) ◽  
Author(s):  
SI Jundong ◽  
LU Mian ◽  
WU Zhijun ◽  
LI Fanxiu
Keyword(s):  
Water Quality ◽  
Quality Evaluation ◽  
Water Environment ◽  
Evaluation Process ◽  
Scientific Basis ◽  
Interval Number ◽  
Set Pair Analysis ◽  
Analysis Model ◽  
Water Quality Evaluation ◽  
Pair Analysis

Aiming at the problem of losing information when the monitoring value is averaged during the water quality evaluation process, the method of converting the interval number into the contact number is proposed, and the interval number model of the set pair analysis number is established. The model was applied to the Fenhe River for water quality evaluation. The evaluation results were basically consistent with the results of the interval clustering method, and the value of i had no effect on the water quality evaluation results when [0,1]. The model calculation process in this paper is simple and fast, and the evaluation results are feasible and effective, which provides a scientific basis for water environment management.

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