Analysis of groundwater quality using fuzzy synthetic evaluation

Dahiya, Sudhir; Singh, Birbal; Gaur, Shalini; Garg, V.K.; Kushwaha, H.S.

doi:10.1016/j.jhazmat.2007.01.119

Cited by 203 publications

(88 citation statements)

References 15 publications

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“…Thus, in recent years, there has been an increasing interest by researchers in analyzing such complex data using robust mathematics and statistical techniques, such as fuzzy comprehensive evaluation method (FCA), cluster analysis (CA), discriminant analysis (DA), and principal component analysis/factor analysis (PCA/FA), and absolute principal component score-multiple linear regression (APCS-MLR) [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28]. A literature review of these methods is described below.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, Liou et al [10] proposed a fuzzy index model for environmental quality evaluation, and proved that the model was flexible and adaptable for evaluating the eutrophic status of reservoir waters. A study conducted by Dahiya et al [12] used FCA to assess the physico-chemical quality of groundwater for drinking purposes. The acceptability of the drinking water was determined based on the limit of different quality classes prescribed by regulatory bodies and the perception of the experts in the field.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-Temporal Variations and Source Apportionment of Water Pollution in Danjiangkou Reservoir Basin, Central China

Chen

Lan

Zhang

2015

Water

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Understanding the spatio-temporal variation and the potential source of water pollution could greatly improve our knowledge of human impacts on the environment. In this work, data of 11 water quality indices were collected during 2012-2014 at 10 monitoring sites in the mainstream and major tributaries of the Danjiangkou Reservoir Basin, Central China. The fuzzy comprehensive assessment (FCA), the cluster analysis (CA) and the discriminant analysis (DA) were used to assess the water pollution status and analyze its spatio-temporal variation. Ten sites were classified by the high pollution (HP) region and the low pollution (LP) region, while 12 months were divided into the wet season and the dry season. It was found that the HP region was mainly in the small tributaries with small drainage areas and low average annual discharges, and it was also found that most of these rivers went through urban areas with industrial and domestic sewages input into the water body. Principal component analysis/factor analysis (PCA/FA) was applied to reveal potential pollution sources, whereas absolute principal component score-multiple linear regression (APCS-MLR) was used to identify their contributions to each water quality variable. The study area was found as being generally affected by OPEN ACCESSWater 2015, 7 2592 industrial and domestic sewage. Furthermore, the HP region was polluted by chemical industries, and the LP region was influenced by agricultural and livestock sewage.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Variations and Source Apportionment of Water Pollution in Danjiangkou Reservoir Basin, Central China

Chen

Lan

Zhang

2015

Water

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“…In max-min operator, the minimum value from each rule is taken and stored in a group using fuzzy min operator and then by choosing the maximum value from that group gives the belongingness of that water sample quality to the specific category [2].…”

Section: Resultsmentioning

confidence: 99%

Analysis of Groundwater Quality using Mamdani Fuzzy Inference System (MFIS) in Yazd province, Iran

Saberinasr¹,

Rezaei²,

Barmaki³

2012

IJCA

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Precise classification and identification of groundwater quality is an essential task for meeting the goals of environmental management. Traditional classification methods of the water quality parameters use crisp set with prescribed limits of various organization. One of the decision making problems about water quality using methods is facing various uncertainties. Recent years have proven fuzzy-logicbased methods capability controlling uncertainties in different environmental problems. The present study utilized a newly devised Mamdani fuzzy inference system to assess groundwater quality in Yazd province. This method made use of 10 measured chemical parameters in 60 samples of groundwater. The samples were collected from wells, springs and kanats. The results showed that 20 groundwater samples were in the "Desirable" class with a certainty level of 32.29-100%, and 20 samples were in the "Acceptable" group with a certainty level of 37.07-92%, and 20 samples were in the "Non-acceptable" category with a certainty level of 43.33-88.78% for potable purposes.

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“…Zadeh, an U.S.expert in control theory [43] , and the contributions of multiple related factors are comprehensively considered according to weight factors, and the fuzziness is decreased by using membership functions [44,45] which is suitable for making decisions in vague and imprecise system. FCE has been widely applied in many fields, such as environmental field [46,47] , agriculture field [43,48] , engineering field [49,50] , and other fields [45,[51][52][53] as well as to solve the fuzzy and difficult to quantify characteristics of the problem [54] . Water quality management is characterized by imprecision in objectives and water quality standards.…”

Section: Assessment Methods Of Surface Watermentioning

confidence: 99%

Hydrochemical Characteristics and Water Quality Assessment of Surface Water at Xiahe County in Tibetan Plateau Pastoral of China

Zhang

Wang

Yousaf

et al. 2016

Preprint

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Water quality assessment in pastoral of Tibetan Plateau, which is water sources for about 40% of world's population and the runoff-yield area of Yellow rivers, is very important. In this paper, Xiahe county which belongs to Tibetan Plateau pastoral was investigated. Six parameters(via, chloride, COD, ammonia nitrogen, nitrate, fluoride, sulfate) were selected to assess the water quality and health degree by using fuzzy comprehensive evaluation methods. The hydrochemical type in surface water was of HCO3 --Mg 2+ -C a2+ type. The cations and anions in surface water were mainly from weathering and dissolution of carbonate rock. Results showed that the water quality in all 69 sampling sites was all of class Ⅰ. The integrated health degree reached more than 0.85 and the health rate were 100%. Although ammonia nitrogen was regarded as the main contamination factor, but it had a little effect on the entire body of water. Overall, the surface water qualities of most samples in Xiahe County was good condition.

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Analysis of groundwater quality using fuzzy synthetic evaluation

Cited by 203 publications

References 15 publications

Spatio-Temporal Variations and Source Apportionment of Water Pollution in Danjiangkou Reservoir Basin, Central China

Spatio-Temporal Variations and Source Apportionment of Water Pollution in Danjiangkou Reservoir Basin, Central China

Analysis of Groundwater Quality using Mamdani Fuzzy Inference System (MFIS) in Yazd province, Iran

Hydrochemical Characteristics and Water Quality Assessment of Surface Water at Xiahe County in Tibetan Plateau Pastoral of China

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