Water Quality Monitoring Index And Section Optimization Of Provincial Buffer Zone In Songhua River Basin

Based on the data of the water quality of the Songhuajiang River Basin,the present situation of the water environment in the buffer zone of the Songhuajiang River Basin was analyzed by using the data of the water quality status of the Songhuajiang River Basin in 2007to 2015.Based on the principal component analysis and K-means clustering method is used to optimize the monitoring index and monitoring section of water environment.The main five monitoring sections of the provincial boundary buffer zone?Golden Snake Bay Terminal,Liangjiazi hydrological station,Linhai,Linhai and Songlin?of Songhua River Basin were selected to monitor and analyze water quality in 2007-2015.According to the data of the long history of water quality monitoring,the single factor pollution index method and the Nemero pollution index method were used to evaluate the current situation of the water environment.The trend of water quality was changed by statistically consistent with or better than III water quality ratio and annual variation coefficient analysis.The main pollutants were NH₃-N,COD_Mn,TP,BOD₅,and the main pollutants were water quality,mainly to organic pollution,the pollution situation lasted longer.The main pollution factor concentration and its interannual variation of water quality are not significant,which indicates that the water quality control effect of the provincial buffer zone is not obvious in the Songhua River basin,and the water quality problem needs to be solved urgently.13 indicators of conventional physical and chemical indicators?pH,DO,COD,BOD₅,NH₃-N,TP,Cu,Zn,fluoride,Se,As,fecal coliforms?and high water quality monitoring were selected for the four main rivers?Songhua River,Second Songhua River,Nenjiang and Suifenhe?in the provincial buffer zone of the Songhua River Basin in 2015,and fecal coliforms were used as metadata.The water quality index was optimized by spss 21.0 software combined with principal component analysis.The water quality of the watershed was identified by seven water quality monitoring indicators,such as Cu,Se,COD,BOD₅,NH₃-N,TP,and As.In order to achieve the optimization of the Songhua River water quality monitoring indicators provincial boundary buffer.Based on K-means clustering analysis and fuzzy clustering analysis,50 water quality monitoring sections of water quality monitoring section of provincial and western buffer zone of Songhua River Basin were optimized by spss 21.0 and MATLAB software.Based on K-means clustering analysis,Section to delete,merge and add.On the basis of the results,the fuzzy clustering analysis results are analyzed.After optimization,from the original 50monitoring section,is preferably 32,which added six sections,greatly reducing the monitoring workload,saving the monitoring costs,improve the efficiency of water quality supervision work.