Comparative Assessment of Various Water Quality Indices (WQIs) in Polyphytos Reservoir-Aliakmon River, Greece

Zotou, Ioanna; Tsihrintzis, Vassiliοs A.; Gikas, Georgios D.

doi:10.3390/proceedings2110611

Cited by 25 publications

(23 citation statements)

References 21 publications

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“…For instance, the determination of water quality status was estimated through the WQI method for Dokan Lake, Kurdistan region, Iraq, where 10 parameters (pH, turbidity, DO, EC, TH, alkalinity, Na + , BOD, NO 3− , and TDS) have been applied by Alobaidy et al [156]. Furthermore, as with Zotou et al [157] 13 water quality parameters were taken into consideration, in applying the specific WQI and in determining their quality status: pH, NO 3− , DO, EC, TSS, turbidity, T, NH 4+ , BOD, COD, NO 2− , TKN (total Kjeldahl nitrogen), and TP (total phosphorus).…”

Section: Selection Of Alternativesmentioning

confidence: 99%

Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review

Akhtar

Ishak

Ahmad

et al. 2021

Water

149

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Human activities continue to affect our water quality; it remains a major problem worldwide (particularly concerning freshwater and human consumption). A critical water quality index (WQI) method has been used to determine the overall water quality status of surface water and groundwater systems globally since the 1960s. WQI follows four steps: parameter selection, sub-indices, establishing weights, and final index aggregation, which are addressed in this review. However, the WQI method is a prolonged process and applied to specific water quality parameters, i.e., water consumption (particular area and time) and other purposes. Therefore, this review discusses the WQI method in simple steps, for water quality assessment, based on two multi-criteria decision-making (MCDM) methods: (1) analytical hierarchical process (AHP); and (2) measuring attractiveness by a categorically based evaluation technique (MACBETH). MCDM methods can facilitate easy calculations, with less effort and great accuracy. Moreover, the uncertainty and eclipsing problems are also discussed—a challenge at every step of WQI development, particularly for parameter selection and establishing weights. This review will help provide water management authorities with useful knowledge pertaining to water usage or modification of existing indicators globally, and contribute to future WQI planning and studies for drinking, irrigation, domestic, and industrial purposes.

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Section: Selection Of Alternativesmentioning

confidence: 99%

Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review

Akhtar

Ishak

Ahmad

et al. 2021

Water

149

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“…Regarding the nitrogen series in all samplings, the predominance of nitrate over ammoniacal nitrogen was observed, suggesting a polluting event from ancient or distant sources (Cassanego, 2017;Zotou et al 2018). This condition may be justified by the fact that the water flow in this river is slow and it has already received domestic sewage for many years.…”

Section: Discussionmentioning

confidence: 85%

“…The high concentration of phosphates is a concern in this study, since, as well as the nitrogen-derived compounds, phosphates in the marine environment can contribute to the eutrophication of the ecosystem (CETESB, 2007) and cause the proliferation of toxic algae, with direct effects on biocenosis (Zotou et al 2018). In addition, eutrophication may hinder recreational activities on Enseada beach.…”

Section: Discussionmentioning

confidence: 99%

Influence of pluviosity and floating population on the water quality of a neotropical costal river

Camargo

Cara

Andrade

et al. 2020

RSD

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The contamination of waterbodies is a worldwide concern due to the increasing urbanization and industrialization of the cities without good effluent management. Touristic cities can suffer with the number of people during high seasons periods, which can lead to an elevated use of natural resources and effluents discharges. Moreover, raining seasons, either high or low, can also play an important role in contaminating waterbodies once a dilution or concentration of contaminants may take place. The present study evaluated the water quality of the Tejereba River (Guarujá, Brazil) during the high season (January) and low season (March and May) in 2018. Reduction in water quality was observed in May, a month with low pluviosity and low tourism. The integrated data analysis (PCA) showed a positive correlation between the physicochemical parameters and the month of May, in which they were negatively correlated with pluviosity and the percentage of tourists. Despite the deterioration of water quality in May, no toxicity to Daphnia magna was observed. Our work showed that water quality (physicochemical and microbiological parameters), during the studied months, is more related to raining seasons than to the presence of tourists in Guarujá, Brazil.

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“…Many reviews about water quality indexing have been published by a variety of authors. For instance 1 , reviewed WQIs developed from 1960 to 2010; 2 analyzed the performance of 30 existing WQIs; 3 , 4 applied 7 different WQIs for, respectively, thirteen and sixteen months monitoring data in river waters; and 5 reviewed 40 existing WQIs. The following statements were extracted from their conclusions: (i) although many WQIs are available, there is still a need of an overall WQI, able to incorporate the available data and describe the water quality for different uses; (ii) significant discrepancies were observed in classification from different methodologies; (iii) the most challenging aspect is that WQIs are developed for a specific region, being source-specific; (iv) no single WQI has been globally accepted; (v) there is no worldwide accepted method for implementing the steps used for developing a WQI; (vi) there is a continuing interest to develop accurate WQIs that suit a local or regional area; (vii) some future directions are still necessary due to the limitations of worldwide developed WQIs.…”

Section: Introductionmentioning

confidence: 99%

“…The multiplicative formula to produce a single WQI-NSF value, operates the dimensionless subindex raised to a power, or the weight of importance of each variable. More recently, in 2001, emerged the WQI-CCME 23 , 24 , a statistical index to assess the quality of surface waters, very well-known and applied worldwide as it was proposed 3 , 4 , 13 , 14 , 25 – 35 ; also applied after receiving some adaptation for local conditions 36 , 37 . The index 23 was proposed with the support of the Canadian Council Minister of Environment, with the following characteristics: it is independent of dimensionless sub-indices; can incorporate from four to all measured parameters; all parameters had the same degree of importance, and had to be measured during four monitoring campaigns.…”

Section: Introductionmentioning

confidence: 99%

Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses

Filho

Oliveira

2021

Sci Rep

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This work elaborated a groundwater quality index—GWQI, for the aquifers of the state of Bahia, Brazil, using multivariable analyses. Data from 600 wells located in the four hydrogeological domains: sedimentary, crystalline, karstic, and metasedimentary, were subjected to exploratory statistical analysis, and 22 out of 26 parameters were subjected to multivariable analysis using Statistica (Version 7.0). From the PCA, 5 factors were sufficient to participate in the index, due to sufficient explanation of the cumulative variance. The matrix of factorial loads (for 1–5 factors) indicated 9 parameters related to water quality and 4 hydrological, with factor loads above ± 0.50, to be part of the hierarchical cluster analysis. The dendrogram allowed to choose the 5 parameters related to groundwater quality, to participate in the GWQI (hardness, total residue, sulphate, fluoride and iron). From the multivariable analyses, three parameters from a previous index—NGWQI, were not selected for the GWQI: chloride (belongs to the hardness hierarchical group); pH (insignificant factor load); and nitrate (significant factor load only for 6 factors), also, not a regionalized variable. From the set of communality values (5 factors), the degree of relevance of each parameter was extracted. Based on these values, were determined the relative weights (wi) for the parameters. Using similar WQI-NSF formulation, a product of quality grades raised to a power, which is the weight of importance of each variable, the GWQI values were calculated. Spatialization of 1369 GWQI values, with the respective colors, on the map of the state of Bahia, revealed good correlation between the groundwater quality and the index quality classification. According to the literature on water quality indexing, the GWQI developed here, using emerging technologies, is a mathematical tool developed as specific index, as it was derived using limits for drinking water. This new index was tailored to represent the quality of the groundwater of the four hydrogeological domains of the state of Bahia. Although it has a regionalized application, its development, using, factor analysis, principal component analysis, and hierarchical cluster analysis, participates of the new trend for WQI development, which uses rational, rather than subjective assessment. The GWQI is a successful index due to its ability to represent the groundwater quality of the state of Bahia, using a single mathematical formulation, the same five parameters, and unique weight for each parameter.

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Comparative Assessment of Various Water Quality Indices (WQIs) in Polyphytos Reservoir-Aliakmon River, Greece

Cited by 25 publications

References 21 publications

Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review

Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review

Influence of pluviosity and floating population on the water quality of a neotropical costal river

Development of a groundwater quality index: GWQI, for the aquifers of the state of Bahia, Brazil using multivariable analyses

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