scholarly journals An abnormal phenomenon in entropy weight method in the dynamic evaluation of water quality index

2021 ◽  
Vol 131 ◽  
pp. 108137
Author(s):  
Wang Zhe ◽  
Xing Xigang ◽  
Yan Feng
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Entropy Weight ◽  
Dynamic Evaluation ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Abnormal Phenomenon

scholarly journals Evaluation of Groundwater Using an Integrated Approach of Entropy Weight and Stochastic Simulation: A Case Study in East Region of Beijing

2021 ◽  
Vol 18 (14) ◽  
pp. 7703
Author(s):  
Yongxiang Zhang ◽  
Ruitao Jia ◽  
Jin Wu ◽  
Huaqing Wang ◽  
Zhuoran Luo
Keyword(s):  
Water Quality ◽  
Stochastic Simulation ◽  
Water Quality Index ◽  
Quality Index ◽  
Integrated Approach ◽  
Total Hardness ◽  
Chemical Components ◽  
Wet Season ◽  
Entropy Weight ◽  
Weakly Alkaline

Groundwater is an important source of water in Beijing. Hydrochemical composition and water quality are the key factors to determine the availability of groundwater. Therefore, an improved integrated weight water quality index approach (IWQI) combining the entropy weight method and the stochastic simulation method is proposed. Through systematic investigation of groundwater chemical composition in different periods, using a hydrogeochemical diagram, multivariate statistics and spatial interpolation analysis, the spatial evolution characteristics and genetic mechanism of groundwater chemistry are discussed. The results show that the groundwater in the study area is weakly alkaline and low mineralized water. The south part of the study area showed higher concentrations of total dissolved solids, total hardness and NO3−-N in the dry season and wet season, and the main hydrochemical types are HCO3−-Ca and HCO3−-Ca-Mg. The natural source mechanism of the groundwater chemical components in Chaoyang District includes rock weathering, dissolution and cation exchange, while the human-made sources are mainly residents and industrial activities. Improved IWQI evaluation results indicate that water quality decreases from southwest to northeast along groundwater flow path. The water quality index (WQI) method cannot reflect the trend of groundwater. Sensitivity analysis indicated that the improved IWQI method could describe the overall water quality reliably, accurately and stably.

scholarly journals Entropy weight application for calculating groundwater quality index (EWQI) in groundwater quality zoning in Pleistocene aquifer in the Phu My town, Ba Ria – Vung Tau province

2020 ◽  
Vol 4 (1) ◽  
pp. 140-148
Author(s):  
Nguyen Hai Au ◽  
Tran Minh Bao ◽  
Pham Thi Tuyet Nhi ◽  
Tat Hong Minh Vy ◽  
Truong Tan Hien ◽  
...  
Keyword(s):  
Water Quality ◽  
Groundwater Quality ◽  
Quality Index ◽  
Animal Husbandry ◽  
Quality Parameters ◽  
Entropy Weight ◽  
Groundwater Quality Index ◽  
Pleistocene Aquifer ◽  
Groundwater Samples ◽  
Entropy Weight Method

Groundwater in Phu My town is exploited essentially in Pleistocene aquifer and, used for many purposes like irrigation, domestic, production and animal husbandry. In this study, Groundwater Quality Index (EWQI) is calculated with Entropy weight method to determine the suitability of groundwater quality in study area. This method demonstrates the objectivity of each parameter calculated based on the degree of variability of each value and depends on the sample data source. The groundwater samples were collected from 17 wells in dry and wet seasons in 2017 with ten water quality parameters (pH, TDS, TH, Cl-, F-, NH4+-N, NO3--N, SO42-, Pb và Fe2+) were selected for analysising. The analysis results indicate groundwater quality is divided into 4 categories in this study area. In particular, over 70% of wells are "very good" water quality in both dry and wet seasons. Only 6% of wells are " water unsuitable for drinking purpose" of the total number of mornitoring wells in the study area.

scholarly journals Remote sensing inversion of lake water quality parameters based on ensemble modelling

2020 ◽  
Vol 143 ◽  
pp. 02007
Author(s):  
Li Xiaojuan ◽  
Huang Mutao ◽  
Li Jianbao
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Entropy Weight ◽  
Ensemble Modelling ◽  
Chl A ◽  
Inversion Model ◽  
Entropy Weight Method ◽  
Weight Method

In this paper, combined with water quality sampling data and Landsat8 satellite remote sensing image data, the inversion model of Chl-a and TN water quality parameter concentration was constructed based on machine learning algorithm. After the verification and evaluation of the inversion results of the test samples, Chl-a TN inversion model with high correlation between model test results and measured data was selected to participate in remote sensing inversion ensemble modelling of water quality parameters. Then, the ensemble remote sensing inversion model of water quality parameters was established based on entropy weight method and error analysis. By applying the idea of ensemble modelling to remote sensing inversion of water quality parameters, the advantages of different models can be integrated and the precision of water quality parameters inversion can be improved. Through the evaluation and comparative analysis of the model results, the entropy weight method can improve the inversion accuracy to some extent, but the improvement space is limited. In the verification of the two methods of ensemble modelling based on error analysis, compared with the optimal results of a single model, the determination coefficient (R2) of Chlorophyll a and TN concentration inversion results was increased from 0.9288 to 0.9313 and from 0.8339 to 0.8838, and the root mean square error was decreased from 14.2615 μ/L to 10.4194 μ/L and from1.1002mg/L to 0.8621mg/L. At the same time, with the increase of the number of models involved in the set modelling, the inversion accuracy is higher.

Integrated Fuzzy Evaluation of Raw Water Eutrophication Based on GIS

2014 ◽  
Vol 580-583 ◽  
pp. 2350-2353
Author(s):  
Jun Ping Liu ◽  
Jia Wei Shao ◽  
Fei Long Dong ◽  
Xiao Yan Ma
Keyword(s):  
Water Quality ◽  
Fuzzy Evaluation ◽  
Raw Water ◽  
Entropy Weight ◽  
Chl A ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Water Plants ◽  
Water Eutrophication ◽  
Quality Indexes

To do a research about raw water eutrophication of water plants in Hangzhou, samples of raw water in Jiuxi, Xiangfu, Nanxing, Qingtai Plant were collected and analyzed to get more than 10 water quality indexes. Turbidity, DO, COD, TN, NH3-N and CHL-a serving as example. supported by GIS, integrated fuzzy evaluations of raw water eutrophication in July and December were completed applying entropy weight method. The result shows that in terms of the nutrient degree, Xiangfu is the most qualified while the least one is Qingtai. Overall, raw water in December is of higher quality than July.

scholarly journals Comparing the results of water quality assessment by fuzzy comprehensive evaluantion method and the water quality index: a case study in the Dong Nai river

2014 ◽  
Vol 17 (2) ◽  
pp. 40-49
Author(s):  
Tran Hoang Bao Le ◽  
Ly Dinh Che ◽  
Than Hien Nguyen
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Urban Areas ◽  
Quality Index ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Water Quality Assessment ◽  
Entropy Weight ◽  
Pollution Levels

The Dong Nai river is a source of supplying water for Ho Chi Minh city, Bien Hoa city and industrial areas. However, the status of the Dong Nai river has been seriously polluted which were caused by emission sources from urban areas, industrial zones, etc. In this study, the fuzzy comprehensive evaluation model (FCE) based on Entropy weight method was built to calculate pollution levels for 18 monitoring sites of the Dong Nai river with 7 parameters in the period 2005 – 2012. The results of study showed that the water quality of section 1 and section 2 are I level which mean good level. Section 3 is III ranking – medium pollution and section 4 is II ranking – slight pollution. Besides, the study also compared the results of the water quality between FCE and the water quality index (WQI). The results indicated that there isn’t difference between two methods. However, the FCE method is more practical, reasonable and acceptable. FCE was less affected by abnormal values than WQI.

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