Water Quality Evaluation And Eutrophication Analysis Of Dongping Lake After The Commissioning Of The Eastern Route Of South-to-North Water Diversion Project

Dongping Lake,as an important water transfer channel and storage hub of the eastern route of South-to-North Water Diversion Project,is not only an important water source for the eastward transmission of water in Shandong Province,but also a basic guarantee for the ecological protection and high-quality development of the Yellow River Basin,and has an extremely important strategic position in the"Blue and Yellow Strategy"for water allocation.The water quality monitoring,evaluation and eutrophication analysis of Dongping Lake will not only provide accurate data for the operation of the South-North Water Transfer Project,but also provide a basis for the implementation of the pollution control plan of Dongping Lake.During the period of 2013-2020 after the commissioning of the eastern route of South-to-North Water Diversion Project,a total of 15 spatial monitoring of water quality was conducted on Dongping Lake.In this study,we first conducted statistical analysis of water quality monitoring data,identified the main pollutants of Dongping Lake,and conducted principal component regression analysis of key indicators to explore their main driving indicators.Secondly,seven indicators of COD,total phosphorus,total nitrogen,ammonia nitrogen,permanganate index,BOD₅ and fluoride were selected as water quality evaluation indicators,and the modified Nemero index method and ABC-LM neural network evaluation model were used to make a comprehensive evaluation and trend analysis of Dongping Lake water quality.Finally,the eutrophic status of Dongping Lake was analyzed by the integrated nutrient index method,and the main driving indicators of the more severe eutrophic years were explored by the principal component analysis.The main results are as follows:（1）Single factor statistical method and principal component regression method were used to analyze the water quality data of Dongping Lake from 2013 to 2020,and the results showed that:TN and TP were the main pollutants of Dongping Lake,and the condition in spring was better than that in autumn,and the overall trend was slowly increasing;the main impact indicators of TP in autumn are fluoride,conductivity and transparency;the main impact indicators of TN in autumn are water depth and p H;the main impact indicators of Chl-a in autumn are p H,water temperature,transparency and water depth.（2）The ABC-LM neural network water quality evaluation model was constructed,and the performance was compared with the self-learning network and L-M network.The results showed that:The ABC-LM network evaluation model outperformed the other two networks in terms of finding speed,avoiding local optimum and over-fitting,and was more accurate for water quality evaluation.（3）The water quality and eutrophication status of Dongping Lake from 2013 to 2020were evaluated by using modified Nemero index method,ABC-LM network model and integrated nutrient index method,and the results showed that:the overall Nemero index of Dongping Lake showed a fluctuating decreasing trend,better in spring than in autumn,and the whole lake basically met the requirements of Class III water;the integrated nutrient index of Dongping Lake was stable and not eutrophic in spring,and there was mild eutrophication in autumn,but the integrated nutrient index fluctuated decreasing.（4）Principal component analysis was performed to identify the main driving indicators of eutrophication in the fall of the more severe eutrophication years,and the results showed that:in 2013,the main driving indicators were water depth,water temperature,transparency,and TN;in 2015,the main driving indicators were TP,Chl-a,p H,and transparency;in 2016,the main driving indicators were dissolved oxygen,conductivity,COD,TP,and p H;in 2018,the main driving indicators were transparency,Chl-a,and water temperature;in 2019,the main driving indicators were transparency,permanganate index,and TP.