Water bloom is one of the most serious ecological environmental problems, which threaten the health of human being and local ecosystems. In this study, we took Lake Taihu in China as the study area,and accessed the occurrence risk of blue-green algae blooms comprehensively based on the individual site,combining self-organizing feature map neural network and fuzzy risk assessment method.Then We exploited the blue-green algae bloom risk zoning and draw the zoning map based on the individual site specific blue-green algae bloom risk assessment through GIS geological statistics analysis method. The assessment results showed that the whole Lake Taihu was divided into four risk zones: sever zone, moderate zone, mild zone and none risk zone, distributing along the aclinic aspect of the slope from northwest to southeast. As a whole, 3/5 of Lake Taihu faced blue-green algae bloom occurrence risk and only less than 2/5 lake area was little or no risk. The blue-green algae bloom occurrence risk presented an obvious mitigation from the northwest to the southeast, where the most sever risk zone was on the north-west. In summary,this study revealed the spatial distribution of blue-green algae bloom occurrence and these method and result would be helpful to support efficient blue-green algae bloom monitoring and risk management.