Correlation Analysis and Prediction of Water Quality Monitoring Indicators in Urban Rivers
To quickly monitor water quality in urban rivers and effectively track and control pollution sources,19 groups of monitoring data from four water quality monitoring stations are selected in a city to analyze the correlation between conventional water quality indicators and core water quality indicators,and the water quality and the monthly changing trend are examined.Mantel tests and selection method of information theory model are used to determine the conventional indicators with the strongest correlation with core indicators and establish the optimal regression prediction model.It is found that the correlation between the same core and conventional indicators varies from monitoring station to station.Generally,they are in positive correlation with slight fluctuations,i.e.permanganate with turbidity,total nitrogen with dissolved oxygen,ammonia nitrogen with conductivity,and turbidity with chloride.No significant correlation is found between five-day biochemical oxygen demand and total phosphorus with conventional indicators.The analytical results show that a relatively reliable overall regression prediction model can be constructed based on a comprehensive analysis of large amount of effective data from various monitoring stations,and the analysis of water quality monitoring data can provide a basis for decision making of effective water pollution prevention and control measures.
water quality monitoringindex correlationwater environment managementurban river
国家科技期刊平台
NSTL
万方数据
