| As a secondary tributary of the Yellow River and the second largest tributary of the Weihe River,the quality of the water quality of the Beiluo River directly affects the water safety and economic development of cities along the middle and lower reaches of the Yellow River.The number of people employed in agriculture in Beiluo River Basin is more than half of the total population.The high demand for agricultural elements and products in Beiluo River Basin makes the pollution load of agricultural non-point sources huge and difficult to control.Water and soil erosion and water quality in the whole basin are serious.In 1997,the soil erosion modulus of the whole basin was 5073t/(km2·a).In 2017,the water quality in Weiwei section of Beiluo River deteriorated to Class V,and in 2020,after renovation,the water quality in Weiwei section of Beiluo River was still Class V.In this context,Yan ’an and Weinan,two cities along the North Luo River,have been ranked at the bottom of the water environment quality in Shaanxi Province for many times,resulting in a large loss of population in the basin and serious obstacles to social and economic development.Based on this,SWAT model,SPSS software and STATA software were used to simulate the spatio-temporal evolution characteristics and driving mechanism of agricultural non-point source pollutant loads in the Beiluo River Basin from 2008 to 2022.Firstly,SWAT-CUP software was used to rate and verify runoff,sediment,total phosphorus and ammonia nitrogen,and the key source areas of agricultural non-point source pollution load were found by combining the SWAT model and statistical software.Secondly,SPSS software was used to explore the influence of precipitation and sediment on non-point source pollution load,the influence of land use type change on non-point source pollution load,and the influence of household behaviors in key source areas on non-point source pollution.Thirdly,STATA software is used to explore how to enhance farmers’ willingness to participate in non-point source pollution control.Finally,the best management measures in the SWAT model are used to simulate emission reduction in key source areas and find out the best emission reduction plan.The main conclusions of this study are as follows:(1)In terms of spatial and temporal distribution:(1)The interannual load of total phosphorus and total nitrogen showed a downward trend from 2008 to 2020,but significantly decreased in2009 and 2011.(2)Total phosphorus and nitrogen showed the seasonal variation characteristics of high values in early spring,late summer and early autumn,and low values in winter and early summer.(3)The output loads of total phosphorus,total nitrogen and different forms of nitrogen and phosphorus were distributed along the river,and the overall pollution degree gradually increased from upstream to downstream,and the pollution near the main stream was the most serious.(2)In this study,nitrogen and phosphorus loads of different forms per unit area were taken as the only index and natural breakpoint method was used to establish the classification table of agricultural non-point source pollution sources in Beiluo River Basin.According to the classification criteria,the key sources of agricultural non-point source pollution prevention and control are mainly distributed in the west of Dingbian County,the west of Wuqi County,the north of Zhidan County,the south of Luochuan County,the middle of Yijun County,the whole of Heyang County,the whole of Dali County,the northeast of Yintai District,the north of Pucheng County,the south of Huanglong County and the central and eastern parts of Chengcheng County.The control pressure of agricultural non-point source pollution in the southern part of the basin is greater than that in the northern part.(3)In terms of influencing factors:(1)According to the Pearson correlation coefficient of SPSS,there is a significant positive correlation between rainfall and sediment on the total phosphorus and nitrogen load.Precipitation was positively correlated with organic nitrogen,inorganic nitrogen,organophosphorus and inorganic phosphorus,sediment was positively correlated with organic nitrogen,organophosphorus and inorganic phosphorus,and sediment was not correlated with inorganic nitrogen.(2)Combined with the output results of statistical software and SWAT model,the characteristics of land use change under different situations were explored.The results showed that cultivated land was the main contributor to non-point source pollution and the key land use type affecting the change of total phosphorus and total nitrogen.(3)The results of SPSS multiple regression analysis show that: One of the main causes of local agricultural non-point source pollution is that farmers with low education,excessive part-time employment,under 30 years old and over 60 years old,engaging in aquaculture,planting non-food crops,combining sprinkler irrigation with rainwater irrigation,and using sprinkler irrigation to irrigate farmland.Farmers’ participation in technical training,mechanical tillage,hedgerows and comprehensive treatment of straw can effectively reduce non-point source pollution.(4)Pollution control:(1)Coordinated control by upstream and downstream local governments can effectively reduce non-point source pollution.(2)The multiple Logistic regression model was used to prove that the identification of economic benefits and ecological benefits,the degree of government attention,the demonstration effect of village committees,the amount of family wealth,and the mastery of professional skills are important factors for the participation of rural households in the key source areas of non-point source pollution.Driven by economic interests,the government’s attention and the call of the neighborhood committee,the temptation of getting rich quickly and increasing income can enhance the willingness of farmers to participate in non-point sources.(3)Environmental regulation has a moderating effect on farmers’ willingness to participate in non-point source pollution,and the order of regulation is incentive regulation > guidance regulation > constraint mechanism.(4)In this study,the optimal management measures in SWAT were used to set up six scenarios with single measures and three scenarios with multiple measures,respectively,from the aspects of pollutant interception and pollution source reduction,to analyze the non-point source pollution load reduction capability in key source areas of the basin.The simulation results show that the reduction effect of "interception" is greater than that of "source reduction".In the scenario scheme of single measure,10 m vegetation buffer zone has the strongest load reduction ability to non-point source.In the scenario scheme combining various measures,no-tillage + 20% fertilizer reduction + 10 m vegetation buffer zone has the strongest reduction ability.The average reduction rate of total nitrogen and phosphorus load was higher than 40% under three scenarios: setting vegetation buffer zone of 10 m,reducing fertilizer use by 20%+ vegetation buffer zone of 10 m,and no-tillage+ reducing fertilizer use by 20%+ vegetation buffer zone of 10 m.The abatement effect of multiple measures is higher than that of single measures.The optimal scenario is "no tillage + 20%fertilizer reduction + 10 m vegetation buffer zone".Under this scenario,the number of key sources of agricultural non-point source pollution in Beiluo River Basin can be reduced to the greatest extent. |
PDF Full Text Request