【摘要】 为分析桓龙湖水库水质状况、预测水质变化,对桓龙湖水库2014年枯、丰、平水期四个监测断面浮游藻类生物密度和种类进行监测.三个水期共监测到浮游藻类4门6纲9目16科23属,硅藻门所占比例最大,其次是绿藻门、蓝藻门、裸藻门,水库处于中-富营养状态;监测到浮游藻类在枯水期、丰水期和平水期的平均数量分别为8.97×10~2个/m L、7.90×10~2个/m L、5.55×10~2个/m L,水库处于中营养状态.根据2011—2013年水质历史数据运用SPSS建立了多元非线性回归预测模型;根据模型建立以综合营养指数为预警指标的分级预警方案,对其验证结果表明20组预警结果 90%可信,预警方案基本能够达到要求.更多还原

【Abstract】 To analyze and predict the water quality in Huanlong lake reservoir,it were monitored the density and species of planktonic algae in the four monitoring section in the dry season,wet season and normal season during 2014.A total of 4 phyla,6 classes,9 orders,16 families,23 genera phytoplankton were identified from dry season to normal season.M ost of them were Bacillariophyta,followed by Chlorophyta,Cyanophyta and Euglenophyta.Huanlong lake reservoir was in mesotropher-eutropher state.The average number per liter of phytoplankton in the dry season,wet season and normal season was 8.97 × 10~5,7.90 × 10~5 and 5.55 × 10~5 respectively.The reservoir was in the state of mesotropher.According to the historical monitoring data of Huanlong lake reservoir from 2011 to 2013,a prediction model was established by means of nonlinear regression analysis and spss program.According to the model a corresponding classified warning project,which took the comprehensive nutrition index as an index,was set up.The resultsof the verification showed that 90 percent of the 20 group advanced warning results were correct.The advanced warning results can meet the requirement basically.更多还原