摘要
使用神经网络模型预测水质符合不同国家水质标准的抚仙湖藻类生物量。当抚仙湖水质符合国家水质Ⅰ类标准时,浮游植物生物量预测值是40.19×104cell/L,几乎不存在水华暴发风险。当水质符合国家水质Ⅱ类标准时,浮游植物生物量预测值是79.51×104cell/L,水华暴发风险较小。抚仙湖水质降至Ⅲ类甚至劣于Ⅲ类时,浮游植物生物量预测值高于800.12×104cell/L,生物量预测值极高,存在较大的水华暴发风险。
The artificial neural network was used to predict the phytoplankton biomass of Fuxian Lake in different scenarios based on Chinese national water quality standards.The prediction results showed that a low biomass was 40. 19 ×104 cell/L when water quality of the lake accorded withⅠclass of the national water quality standard,which had no risk of algal bloom.The phytoplankton biomass was 79. 5 1 ×104 cell/L when the water quality accorded withⅡclass.It has little risk of algal bloom.However,a significant high abundance of phytoplankton biomass was predicted to 800. 12 ×104 cell/L when the water quality was belowⅢclass,which implied a big risk of the algal bloom.
出处
《环境科学导刊》
2015年第6期4-7,共4页
Environmental Science Survey
基金
云南省环境保护厅"云南省生物多样性保护专项<泸沽湖
洱海
抚仙湖三大高原湖泊水生态调查与评估>项目。"
关键词
神经网络模型
水华暴发
风险
预测
抚仙湖
artificial neural network
algal bloom
risk
predict
Fuxian Lake
