摘要
为了解江门市四堡水库水质状况,在该水库布置了13处采样点,于2018年6-12月进行了7次水样采集和检测工作,分析水质因子时空变化规律。分别采用单因子评价法、BP神经网络法、主成分分析法及指数法等对四堡水库水质和富营养化状况进行综合评价。利用Pearson方法研究叶绿素a与水质因子的相关性,分析影响水库富营养化的主要驱动因子。结果表明:不同月份的总磷、总氮和氨氮变化较为复杂,靠近水库中下游区域的水质较好,水库汇水区的水质较差;单因子评价法和BP神经网络的评价结果大体一致,水库水质总体在Ⅲ~Ⅳ类之间,主成分分析法表明水质主要受高锰酸盐指数、总磷、总氮、氨氮影响,指数法表明水库处于轻度富营养化状态,在水库汇水区的富营养化程度较高;相关性分析表明,叶绿素a与氨氮相关性较强,氮为浮游植物生长的限制因子,控制氮素浓度能够有效地治理水体富营养化。
In order to find out the water quality of the Sibao Reservoir in Jiangmen City,water samples were collected and tested seven times from 13 sampling locations in June to December 2018 to analyze the temporal and spatial variations of water quality factors.The water quality and eutrophication of Sibao Reservoir were evaluated using the single factor evaluation method,BP neural network,principal component analysis method and index method.The Pearson method was used to study the correlation between chlorophyll a and water quality factors,and to analyze the main driving factors affecting reservoir eutrophication.The results indicated that the changes of total phosphorus,total nitrogen and ammonia nitrogen in different months were relatively complicated.The water quality near the middle and lower reaches of the reservoir was better,and that in the catchment area was poorer.The results from the single factor evaluation and BP neural network were consistent,indicating that the water quality of the reservoir was generally between classⅢ~Ⅳ.The principal component analysis showed that the water quality was mainly affected by permanganate index,total phosphorus,total nitrogen and ammonia nitrogen.The results of the index method showed that the reservoir was in a state of mild eutrophic,and the degree of eutrophication in the catchment area was higher.The correlation analysis showed that chlorophyll a had strong correlation with ammonia nitrogen and permanganate index.Nitrogen was the limiting factor for the growth of phytoplankton,and the control of nitrogen concentration could effectively control the eutrophication of water bodies.
作者
傅博
黄国如
FU Bo;HUANG Guoru(School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,China;State Key hiboratory of Subtropical Building Science,South China University of Technology y Guangzhou 510640,China;Guangdong Engineering Technology Research Center of Safety and Greenization for Water Conservancy Project,Guangzhou 510640,China)
出处
《水资源与水工程学报》
CSCD
2019年第5期64-71,共8页
Journal of Water Resources and Water Engineering
基金
广东省水资源节约与保护资金项目(201711031)
关键词
水质时空变化
水质评价
单因子评价法
B
P神经网络
主成分分析
指数法
水库富营养化
spatiotemporal variations of water quality
water quality evaluation
single factor evaluation
BP neural network
principal component analysis
index method
reservoir eutrophication
