Relationship between nutrients and phytoplankton biomass based on chlorophyll prediction model in Zribar Lake of Kurdestan, a case study

Zaribar Lake is a little shallow lake in Kurdistan province of Iran and it is faced to eutrophication.The study of phytoplankton biomass-nutrient relations is important in eutrophication management and there are many empirical models to predict phytoplankton biomass (chlorophyll a) based on nutrient (nitrogen and phosphorous) amounts in the lake. Evaluation of these empirical models and comparing the results with the real chlorophyll of the lake can be determine the proper model to simplifying future study and helps eutrophication management of the lake by giving useful information about chlorophyll-nutrient relations. Hence, sampling to an analysis of nitrogen, phosphorous and chlorophyll was carried out by select 6 sampling sites every two months from September 2010 to July 2011. Results showed that the models cannot predict current amounts of the chlorophyll and predicted amounts of chlorophyll based on nutrient are much more than the real chlorophyll a. Therefor the growth of phytoplankton (chlorophyll a) is limited by another factor such as light and common eutrophication control methods, that are based on limitation of external nutrient loading, are not practical and effective to the lake Zribar. In addition, there should be a new adapted model contained light limiting variable.