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Fuzzy Logic Uses on Eutrophication and Water Quality Predictions

Author(s): G. K. Ellina; I. Kagkalou

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Abstract: The interpretation and prediction of physical, chemical and biological functions taking place in freshwater ecosystems have been studied until today using widely available empirical and dynamic models and multi-criteria analysis methods. The purpose of this study is to investigate the eutrophication factors (temperature, NO 3 -, TP, Secchi depth and chlorophyll-a) in a highly variable system of Lake Karla (Thessaly, Greece) using Fuzzy Logic. Furthermore, we develop suitable methods for Water Quality assessment. Our goal is to decrease uncertainty towards the criteria that are used in decision making tools. More precisely, the factors being studied for the evaluation of water quality in Karla Lake are p H, Total Phosphorus and Nitrogen. In this way we can separate the Fuzzy Water Quality in classes (poor, average and good).

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Year: 2016

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