Sensibility of the Lake Taihu chlorophyll-a assimilation system to different parameters directly control the accuracy of estimate the chlorophyll-a concentration distribution when using this assimilation system. We used multispectral data of Environmental Satellite 1(HJ-1), obtained on April 21st, 2009, combined with in situ data to retrieve the concentration of chlorophyll-a in Lake Taihu. We developed a Lake Taihu chlorophyll-a data assimilation system based on ensemble square root Klaman filter(EnSRF) technique. Take the retrieved chlorophyll-a concentration of Lake Taihu as the initial background value, then combined with the data assimilation system to analyze the influence of the ensemble size, the assimilation time, the background error, the observation error and the model error on the assimilation system. The results indicate:taking the computing cost, time cost of system and the performance of the assimilation system into consideration, the assimilation system performs well when the ensemble size are 30-40; the assimilation system is not very sensitive to the accuracy of estimation of the background; both the observation and the model errors are very important for the performance of the system; different test stations have different water dynamic properties, so they have different performance; the estimation of chlorophyll-a concentration can be improved by using the data assimilation method.