River quality analysis using fuzzy water quality index: Ribeira do Iguape river watershed, Brazil

Lermontov, André; Yokoyama, Lídia; Lermontov, Mihail; Machado, Maria Augusta Soares

doi:10.1016/j.ecolind.2009.02.006

Cited by 198 publications

(105 citation statements)

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“…Their main advantage is to synthesize a complex reality in a single number and to define clear goals (Akkoyunlu and Akiner, 2012;Lermontov et al, 2009;Silva and Jardim, 2006). The ALPI is a classic example of water quality indices: suitable for the protection of the aquatic life that incorporates the most representative parameters, especially toxicity and eutrophication (CETESB, 2013).…”

Section: Discussionmentioning

confidence: 99%

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Aquatic life protection index of an urban river Bacanga basin in northern Brazil, São Luís - MA

et al. 2016

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Bacanga River Basin faces environmental problems related to urbanization and discharge of untreated domestic sewage, which compromise its ecosystem health. Due to the small number of studies that assessed its water quality, the present study aimed to assess the current status of this ecosystem based on the aquatic life protection index. Samples were carried out every two months, in a total of six events, in six sites along the basin, where the water samples were collected to assess physicochemical parameters and calculate the trophic state index and the index of minimum parameters for the protection of aquatic communities. The data were also compared with values determined by the resolution National Environment Council -CONAMA 357/05. Our results reveal significant changes in the water quality of Bacanga River Basin. An increase in nutrients and chlorophyll-a concentration led it to eutrophication. The surfactant values were high and put in danger the aquatic biota. Dissolved oxygen rates were below the values allowed by the resolution in most sites sampled. The current water quality is terrible for the protection of aquatic life in 61.92% of the sites sampled.Keywords: water quality, contamination, domestic sewage. Índice de proteção da vida aquática em uma bacia urbana do rio Bacanga no norte do Brasil, São Luís -MA ResumoA Bacia Hidrográfica do rio Bacanga (BHRB) apresenta problemas ambientais relacionados a urbanização e lançamentos de esgoto in natura que comprometem a qualidade desse ecossistema. Devido ao reduzido número de estudos associados à avaliação da qualidade da água no local, este estudo teve como objetivo avaliar a situação atual desse ecossistema por meio do Índice de Proteção da Vida Aquática. Seis amostragens bimestrais foram realizadas em seis pontos ao longo da bacia, coletando parâmetros físico-químicos para a aplicação do Índice de Estado Trófico e Índice de Parâmetros Mínimos para a Proteção da Vida Aquática, relacionando-os com a resolução Conselho Nacional do Meio Ambiente -CONAMA/357. Os resultados revelaram alterações significativas na qualidade da água da BHRB, o aumento de nutrientes e das concentrações de clorofila-a conduziram ao um estado geral de eutrofização. Os valores de surfactantes foram altos colocando em risco a biota aquática e as taxas de oxigênio dissolvido estiveram abaixo do permitido pela resolução na maioria dos pontos amostrados. A situação atual da qualidade da água para proteção da vida aquática é péssima em 61,92% dos pontos amostrados.Palavras-chave: qualidade da água, contaminação, efluentes domésticos.

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Section: Discussionmentioning

confidence: 99%

“…Indices are considered more reliable than isolate variables, as they can integrate several parameters in a single number (Dobbie and Dail, 2013;Hurley et al, 2012;Abaurrea et al, 2011;Lermontov et al, 2009;Štambuk-Giljanović, 1999).…”

Section: Introductionmentioning

confidence: 99%

Aquatic life protection index of an urban river Bacanga basin in northern Brazil, São Luís - MA

et al. 2016

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“…Fuzzy inference systems are a widespread method in the treatment of information for the generation of expert systems in monitoring the water quality (Nasiri et al, 2007;Lermontov et al, 2009;Hatzikos et al, 2009). Roughly speaking, a fuzzy inference system is an algorithm able to convert a strategy or set of linguistic rules in an automated strategy.…”

Section: Descriptionmentioning

confidence: 99%

Fuzzy expert system for the detection of episodes of poor water quality through continuous measurement

Ángulo¹,

Cabestany²,

Rodríguez³

et al. 2012

Expert Systems with Applications

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In order to prevent and reduce water pollution, promote a sustainable use, protect the environment and enhance the status of aquatic ecosystems, this article deals with the application of advanced mathematical techniques designed to aid in the management of records of different water quality monitoring networks. These studies include the development of a software tool for decision support, based on the application of fuzzy logic techniques, which can indicate water quality episodes from the behaviour of variables measured at continuous automatic water control networks. Using a few physicalchemical variables recorded continuously, the expert system is able to obtain water quality phenomena indicators, which can be associated, with a high probability of cause-effect relationship, with human pressure on the water environment, such as urban discharges or diffuse agricultural pollution. In this sense, at the proposed expert system, automatic water quality control networks complement manual sampling of official administrative networks and laboratory analysis, providing information related to specific events (discharges) or continuous processes (eutrophication, fish risk) which can hardly be detected by discrete sampling.

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“…In Lermontov et al (2009), the interpretation of the final aggregated index was then performed based on the following classification scheme: water quality is interpreted as poor (final index from 0 -19), bad (20 -36), fair (37 -51), good (52 -79) and excellent (80 -100).…”

Section: E) Final Index Value Interpretationmentioning

confidence: 99%

“…In a fuzzy-based index, parameters are normalized and grouped through a Fuzzy Interference System (FIS) wherein the numerical values (inputs) are fuzzified into a qualitative state (outputs) and processed by an inference engine, memberships functions, rules, sets and operators in a qualitative state (Lermontov et al 2009). …”

Section: B) Generation Of Sub-indicesmentioning

confidence: 99%

Development of river water quality indices—a review

Sutadian

Muttil

Yilmaz

et al. 2015

Environ Monit Assess

318

208

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The use of water quality indices (WQIs) as a tool to evaluate the status of water quality in rivers has been introduced since the 1960s. The WQI transforms selected water quality parameters into a dimensionless number so that changes in river water quality at any particular location and time could be presented in a simple and easily understandable manner. Although many WQIs have been developed, there is no worldwide accepted method for implementing the steps used for developing a WQI. Thus, there is a continuing interest to develop accurate WQIs that suit a local or regional area. This paper aims to provide significant contribution to the development of future river WQIs through a review of 30 existing WQIs based on the four steps needed to develop a WQI. These steps are the selection of parameters, the generation of sub-indices, the generation of parameter weights and the aggregation process to compute the final index value. From the 30 reviewed WQIs, 7 were identified as most important based on their wider use and they were discussed in detail. It was observed that a major factor that influences wider use of a WQI is the support provided by the government and authorities to implement a WQI as the main tool to evaluate the status of rivers. Since there is a lot of subjectivity and uncertainty involved in the steps for developing and applying a WQI, it is recommended that the opinion of local water quality experts is taken, especially in the first three steps (through techniques like Delphi method). It was also observed that uncertainty and sensitivity analysis was rarely undertaken to reduce uncertainty and hence such an analysis is recommended for future studies.

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River quality analysis using fuzzy water quality index: Ribeira do Iguape river watershed, Brazil

Cited by 198 publications

References 20 publications

Aquatic life protection index of an urban river Bacanga basin in northern Brazil, São Luís - MA

Aquatic life protection index of an urban river Bacanga basin in northern Brazil, São Luís - MA

Fuzzy expert system for the detection of episodes of poor water quality through continuous measurement

Development of river water quality indices—a review

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