Fuzzy models with GIS for water quality diatom-indicator classification

The level of certain or set of physico-chemical parameter(s) determinates the optimal living condition for the organism. These thresholds in biology are express using categories of classes. One such category which consists from five classes is water quality (WQ) category based on Saturated Oxygen. Due to natural or human-made pressure on the ecosystem, bottom line as that we have to monitor the levels. Many of the diatoms are very sensitive to certain parameters and for these diatoms ecological indicator reference are known in the literature. But, there are many other unknown ecological references to be identified especially for the newly discovered diatoms. The diatom measurement data is noisy, usually comprises from several dimensions and also has non-linear relationship between the environmental parameters and the diatoms abundance. All these properties of the diatom dataset do not meet the assumptions of conventional statistical procedures. To overcome these problems, this research aims to a fuzzy classification approach to describe this diatom-indicator relationship. Using the approach, each diatom will be classified and together with the Geographic Information System (GIS) software, will be represented on map based on Saturated Oxygen parameter. The results from the model are verified with the known ecological reference found in the literature. Even more important, the proposed method has added some new ecological references that do not exist. This fuzzy approach can be modified for defining new WQ category classes based not only for Saturated Oxygen parameters, but also for metals and other physico-chemical parameters.