Inderscience Publishers

Data mining techniques for water ecotoxicity classification for application on water resources management

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Among the various forms of action that promote sustainability, technological innovation can be considered one of the most important. This paper applied data mining techniques to discover knowledge in the field of water quality monitoring data, providing useful and relevant support for decision-making in environmental management systems. At the current stage of research, a predictive modelling technique, known as rule-based classification, was used to find rules that can, based on the values of certain chemical parameters, predict the ecotoxicity level of a water sample. We used data from water analyses from main water bodies of São Paulo state in Brazil, from 2005 to 2010. We expect to get a reliable, fast and effective way to predict the ecotoxicity levels of water in rivers, lakes and reservoirs based on analyses of chemical parameters, or indicate the complementarity of these measurements for optimisation of monitoring networks and the consequent improvement natural resources management.

Keywords: water quality monitoring, water ecotoxicity, water bodies, chemical parameters, water resources management, sustainable development, Brazil, environmental management systems, knowledge discovery in databases, data mining, predictive modelling, rule-based classification, support for decision-making

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