• 关键词：综合因子  预测  模型  藻华

• 基金项目：国家"十五"科技攻关资助项目(No.2002BA806B04);广东省教育厅自然科学基金资助项目(No.04J009)

• 王志红
• 1. 华南理工大学环境科学研究所, 广州 510641; 2. 广东工业大学建设学院, 广州 510006

• 崔福义
• 哈尔滨工业大学市政环境工程学院, 哈尔滨 150090

• 韦朝海
• 华南理工大学环境科学研究所, 广州 510641

• 陈牧民
• 开平供水集团股份有限公司, 开平 529300

• 摘要：通过人工模拟系统培养藻类,考察了总氮、总磷、水温、pH、光强、水深等因素与藻生长高峰值之间的关系,提出了一个适用于给水处理厂的短期内局部湖区硅藻和绿藻藻生物量的综合因子预测模型.模型建立了综合因子的概念.在实际水样验证中,当水温为30℃时,模型预测值与实测值之间的平均误差为14.6%;当水温为20℃时,平均误差为19.4%.模型有良好的实用性和可操作性.

• Abstract：There is no proper way to predicate maximum algae biomass of an alga bloom many water supply plants, which use lakes or reservoirs as water resources. Through a designed simulating system, algae are cultivated to investigate the relation between the maximum biomass and other factors. This paper proposes a new comprehensive factor model for algae biomass predication in local lake area. In this model, total nitrogen, total phosphorus, water temperature, light intensity, pH and water depth are used to construct the comprehensive factor. And the maximum algae biomass is a function of the comprehensive factor. By applying it to several raw water samples, the model has proved an average accuracy of 14.6% at water temperature 30℃ and 19.4 % at water temperature 20℃.

• Key words：comprehensive factor  predication  model  algae bloom

• 
  摘要点击次数： 2043 全文下载次数： 3314