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Assessing water quality in rivers with fuzzy inference systems: a case study
William Ocampo-Duque1, Núria Ferré-Huguet, José L Domingo
1School of Chemical and Process Engineering, Rovira i Virgili University, Avenida de los Países Catalanes 26, 43007 Tarragona, Spain. waocampo@urv.net
Environment International
|May 9, 2006
Summary
This study introduces a fuzzy inference system (FIS) to create a water quality index, effectively handling environmental data uncertainty. The fuzzy logic approach provides a reliable tool for water management and pollution assessment.
Area of Science:
- Environmental Science
- Water Resource Management
- Computational Intelligence
Background:
- Environmental problems often involve uncertainty and subjectivity, challenging traditional assessment methods.
- Fuzzy logic offers a robust framework for addressing vagueness and imprecision in complex systems.
- Effective water quality assessment is crucial for environmental protection and sustainable resource management.
Purpose of the Study:
- To develop and validate a novel methodology for water quality assessment using fuzzy inference systems (FIS).
- To create a fuzzy water quality index (WQI) that incorporates the relative importance of various water quality indicators.
- To test the applicability of the proposed fuzzy WQI using a case study from the Ebro River, Spain.
Main Methods:
- Development of a fuzzy inference system (FIS) for calculating a water quality index.
- Application of a multi-attribute decision-aiding method to determine the relative importance of water quality indicators within the FIS.
- Validation of the fuzzy WQI using a dataset from the Ebro River and comparison with existing data and expert opinions.
- Integration of findings within a geographic information system (GIS) for spatial analysis.
Main Results:
- A functional fuzzy water quality index was successfully developed and calculated.
- The fuzzy WQI demonstrated strong agreement with official reports and expert assessments of water pollution in the Ebro River.
- The methodology proved effective in managing and interpreting water quality data from multiple sources.
Conclusions:
- The proposed fuzzy inference system-based methodology is a suitable and alternative tool for water quality assessment.
- This approach effectively addresses uncertainty and subjectivity inherent in environmental data.
- The fuzzy WQI can contribute to the development of more effective water management plans and pollution control strategies.
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