a new fuzzy-logic based model for chlorophyll-a in pulicat lagoon, india

coastal lagoons are complex ecosystems exhibiting a high degree of non-linearity in the distribution and exchange of nutrients dissolved in the water column due to their spatio-temporal characteristics. this factor has a direct influence on the concentrations of chlorophyll-a, an indicator of the primary productivity in the water bodies as lakes and lagoons. moreover the seasonal variability in the characteristics of large-scale basins further contributes to the uncertainties in the data on the physico-chemical and biological characteristics of the lagoons. considering the above, modelling the distributions of the nutrients with respect to the chlorophyll-concentrations, hence requires an effective approach which will appropriately account for the non-linearity of the ecosystem as well as the uncertainties in the available data. in the present investigation, fuzzy logic was used to develop a new model of the primary production for pulicat lagoon, southeast coast of india. multiple regression analysis revealed that the concentrations of chlorophyll-a in the lagoon was highly influenced by the dissolved concentrations of nitrate, nitrites and phosphorous to different extents over different seasons and years. a high degree of agreement was obtained between the actual field values and those predicted by the new fuzzy model (d = 0.881 to 0.788) for the years 2005 and 2006, illustrating the efficiency of the model in predicting the values of chlorophyll-a in the lagoon.