A fuzzy inference system modeling the interactions among environmental stressors in the ecosystem of Lake Koronia, Greece

摘要

The development of a model for assessing stressor impacts and interactions in the ecosystem of Lake Koronia, based on Fuzzy Inference, is presented in this paper. The proposed fuzzy inference model assesses the combined effect of the interactions among the most significant stressors on the fish population of the lake, i.e. industrial pollution, pesticide and nutrient usage due to agricultural activities and water level decrease due to irrigation works. Apart from the experts' knowledge, expressed in a set of fuzzy rules, a number of parameters such as pH, conductivity, Biological and Chemical Oxygen Demand and nitrate concentration were used as stressor indicators. The proposed model is capable of simulating the effect of a large number of environmental conditions and it can be used as a dynamic tool for ecosystem risk assessment since it is capable of producing both qualitative and quantitative results. Its operation was successfully verified for a number of different conditions, ranging from low stressor impact conditions to high stressor impact conditions (where, in fact, the fish population was diminished).