Study On Fuzzy Assessment And Prediction Of Eutrophication For Bohai Bay

Nutrient salt load into sea increased owing to fast rise of population, rapid development of economic and high exploitation of coast. It aggravated eutrophication of coastal water which has heavily restricted sustainable development of coastal economic. Establishing of assessment model and prediction model for eutrophication will do important signification to repair, management, prevention and cure of coastal water eutrophication.The study in this paper is based on Bohai Bay. Through analyzing main factors related to eutrophication in Bohai Bay and synthesizing chemistry index and phytoplankton index and bacteria index also considered, the method of two-grade fuzzy synthesis assessment for seawater eutrophication is put forward. The method is applied to assess the eutrophication level in Bohai Bay and the result is transformed by weighted-average principle. Through arranging final assessment result,it can be found eutrophication is serious in north costal water and south fishery of Bohai Bay. The level of eutrophication is the highest in summer and lowest in autumn.Phytoplankton distribution differentiation of Bohai Bay in 2004 and 2005 was studied by ecological ordination method, and influence on phytoplankton distribution differentiation by spatial distribution pattern and environment factors was analysed by local CCA ordination method.The influence on phytoplankton distribution differentiation by spatial distribution pattern is lager than by environment factors except in October.In the environment factors, P influenced phytoplankton distribution differentiation most following silicate and salinity. Ecological area in Bohai Bay was partitioned according to the result of ordination.According to areas partitioned by ecological ordination method, red-tide survey and control area was selected to establish fuzzy logic eutrophication model. TN and TP were selected as input of model and the influence of temperature and current chlorophyll was also considered.Fuzzy inference rules were established based on survey data of three stations in red-tide control area. Output of model was fitted by chlorophyll value of these stations which indicated rules are basically satisfied. The other station was simulated and most of the results were close to fact value.