Analysis on Quality Characteristics and Main Influencing Factors of Surface Water in Liangxi River System
In order to comprehensively analyze the surface water quality characteristics of the Liangxi River in Wuxi.This study monitored the changes in water quality in the Hongqiao and Liqiao sections of the Liangxi River from 2020 to 2022.Combined with the change of water quality in Meiliang Bay from 2021 to 2022 and the water quality of eight tributaries at the entrance of Taihu Lake of Liangxi River and the junction of the Beijing-Hangzhou Canal from September to December 2021.This study comprehensively explored the influence of water diversion in Meil-iang Bay and the change of water quality in Liangxi River on the water quality of the main river section.The results showed that the surface wa-ter quality of the Liangxi River system has gradually improved,and its indexes of DO,COD,permanganate,ammonia nitrogen,and total phos-phorus all meet the three kinds of surface water standards.High temperatures in summer will accelerate the aerobic process of the water system,cause the decrease of DO content,and further lead to the increase of COD,permanganate,ammonia nitrogen,and total phosphorus in the water system,which is one of the important factors affecting the water quality of Liangxi River.The contents of ammonia nitrogen and total phosphorus in Meiliang Bay are higher in summer.Combined with the Canoco 5 correlation analysis,it makes a great contribution to the content of ammonia nitrogen and total phosphorus in the Liangxi River.However,the content of COD in Sanjieqiaobang is higher,and the confluence of its branch water flow is one of the factors leading to the high content of organic pollutants in the Liangxi River.It is suggested that the water quality of Li-angxi River should be comprehensively improved from three aspects:the stability of Liangxi River water quality in summer,the control of water diversion in Meiliang Bay,and the treatment of main river water quality.
Liangxi RiverSurface water qualityWater diversionTributaryCorrelation analysis
国家科技期刊平台
NSTL
万方数据
维普
