Analysis Of Non-point Source Pollution Characteristics And BMPs Research In Liuyang River Basin

Non-point source pollution is one of the main reasons for the deterioration of the water environment in the river basin.Taking the corresponding Best Management Practices(BMPs)according to the current situation of river basin pollution and the characteristics of non-point source pollution is to improve the water environment and water quality of the river basin key.A non-point source pollution model in the Liuyang River Basin was established to simulate the spatial and temporal distribution characteristics of non-point source pollution and the loss intensity of pollution loads in different hydrological years.Scenario analysis was used to analyze the reduction effect and environment-cost value of different BMPs measures,and the optimal control measures were selected.The main contents are as follows:(1)Investigation on the current status of water environment in the basin.According to the water quality data from 2010 to 2016,the current situation of the water environment in the basin was analyzed.Based on the pollutant discharge coefficient method,the point source pollution load and non-point source pollution load in the basin are estimated.The results show that non-point source pollution has become one of the main pollution sources in the Liuyang River Basin,and it mainly comes from agricultural planting,rural life and livestock and poultry breeding.(2)Establish a non-point source pollution model in the Liuyang River Basin.SWAT-CUP was used to analyze the sensitivity of runoff,sediment,total phosphorus and ammonia nitrogen,and the sensitive parameters of the model were calibrated and verified according to the measured hydrology and water quality data from 2010 to 2016.The results show that the parameter evaluation indicators R2 and Ens both meet the evaluation criteria,indicating that the model has good applicability in the Liuyang River Basin.(3)Analysis of the characteristics of non-point source pollution in the watershed.Simulate and analyze the temporal changes and spatial distribution of runoff,sediment,total phosphorus and total nitrogen in different hydrological years of the basin,and identify key pollution source areas.The amount of total phosphorus and total nitrogen load loss is significantly affected by rainfall,runoff and land use patterns,and is generally the largest in wet years,followed by flat water years,and the smallest in dry years;the overall non-point source pollution load loss intensity is the largest in the cultivated land area in the upper reaches of the river basin.,the downstream cultivated land area is the second,and the middle reaches of the forest land area is the smallest.According to the pollution load loss intensity,the natural rift classification method was adopted,and seven sub-basins were identified as the key pollution source areas of the watershed.(4)Reduction Efficiency and Environmental-Cost-Benefit Analysis of Different Scenarios.By analyzing the characteristics of non-point source pollution in the watershed,combined with the current situation of watershed pollution,select the corresponding engineering measures and non-engineering measures and conduct a comprehensive analysis of technology and cost.Using the scenario analysis method,five single scenario scenarios and seven scenario combination scenarios are set up,and the reduction efficiency and environmental-cost benefit of each scenario are simulated and analyzed.The results show that,in the single scenario,the reduction efficiency is in the order of returning farmland to forests>planting grass and waterways>contour farming>reducing the amount of chemical fertilizer application by 30%;in the combined scenario scheme,planting grass and waterways+ returning farmland to forest and reducing the amount of chemical fertilizer application by 30%+Planting waterway+returning farmland to forest has the best reduction efficiency.The overall environmental-cost benefit of each scenario shows that engineering measures are higher than non-engineering measures,and the combined scenarios are higher than most single scenarios.