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A new Fuzzy-LOGIC based Model for Chlorophyll-a in Pulicat Lagoon, India | ||
| International Journal of Environmental Research | ||
| مقاله 29، دوره 4، شماره 4، بهمن 2010، صفحه 837-848 اصل مقاله (361.52 K) | ||
| شناسه دیجیتال (DOI): 10.22059/ijer.2010.270 | ||
| نویسندگان | ||
| H. Santhanam1؛ S. Amal Raj* 2 | ||
| 1Centre for Earth Sciences, Indian Institute of Science, Bangalore – 560 012, India | ||
| 2Centre for Environmental Studies, Anna University-Chennai, Chennai 600 025, India | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| Coastal lagoon؛ Pulicat lagoon؛ Chlorophyll-a؛ fuzzy logic؛ Multiple Regression analysis | ||
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