Study On The Simulation Of Non-point Source Pollution In Long River, Three Gorges Reservoir Area

Water shortage has been one of the huge challenges to the global development, the contradictions between the growing population and the increasingly scarce water resources restrict the survival and development of human society. Water resources in China exists two main problems: one is the shortage of water resources, and the other is serious water pollution. Along with the constant governance of environmental protection in our country, point source pollution emissions had been well controlled, but water quality deterioration caused by agricultural non-point source pollution situation is still grim.The Three Gorges Water Conservancy Hub Project on the Yangtze river is currently the world’s largest water conservancy and hydropower project. The completion of the Three Gorges Dam changed basin natural state, made the river bed wider, the flow velocity slowed down, the water self-purification ability significantly reduced, reservoir eutrophication trend was severe. For that reason, Long River, the typical watershed of Three Gorges Reservoir Area(TGRA) was selected as the research area, the distributed hydrological model SWAT was used to simulate the non-point source pollution, find the critical pollutants source area, which can help improve the efficiency of the nonpoint source pollution control. The main research contents and conclusions are as follows:(1)The rainfall regime of study areaThe acquaintance of the rainfall regime of the study area is the premise of watershed hydrology research. Using the linear trend analysis and moving average method, the monthly precipitation during 1951-2012 of a total number of 27 meteorological stations was analyzed. The results show that the annual precipitation and precipitation days in the TGRA showed a trend of decrease. The reduction trend of rainy days was greater than that of precipitation, which means that the average precipitation in rainy days has the trend of increase, short-term heavy rainfall event will increase, which will lead to serious soil erosion and non-point source pollution. The precipitation in rainy season and dry season all showed a trend of reduction. The rainy season precipitation reduction can alleviate the pressure of the basin flood control regulation, but attentions should also be payed to the flood peak caused by the short duration of extreme precipitation events. The precipitation reduction in dry season will pressure the water use for industrial and agricultural production and shipping. The terrain is the important factors that affects the precipitation. Mountain has water vapor block uplift effect, which will help the formation of precipitaion. With the increase of altitude, the precipitation will increase. The precipitation in the TGRA has very close relationship with altitude, every rising of 100 m in altitude, the precipitation will increase 30 mm, so the analysis of spatial distribution of precipitation should fully consider the influence of altitude.(2)Effect of spatial data on the accuracy of SWAT model hydrological simulationDigital Elevatin Model(DEM), landuse type distribution, soil type distribution are the main spatial data needed for SWAT model setup. There are various sources of spatial data with various resolution. Before the setup of SWAT model, the previous research results on the influence of the spatial data on model simulation results were analyzed, which will provide reference for the selection of model data and improve precision of the model simulation. The results shows that the simulation of different objects(flow, sediment and nutrient elements, etc.) exists different upper and lower threshold to most of the spatial data(DEM, land use and soil) resolution. Too high or too low precision of the spatial data are likely to reduce the precision of the model. The response of flow and nitrate nitrogen(NO3-N), sediment and the total phosphorus(TP) to changes in the quality of spatial data are consistent. Subbasin classification number slightly influence the runoff simulation and significantly influence the sediment yield. On the surface runoff simulation, the spatial precipitaion data that can embody the local rainfall events which largely contribute to surface runoff will have a good performance than the precipitation data obtained from meteorological stations. A DEM with 30 m resolution, a landuse datum with 60 m resolution, a soil datum with 1:1Million were chosen to seup the model.(3)SWAT model setup and adaptability evaluationThere are 9 kinds of land cover types, 10 kinds of soil types, and the slope was divided into three grades. 30 subbasins were obtained by the watershed delineation, 1884 Hydrological Response Units(HRU) were obtained by the overlap of land cover, soil and slope. The most senstive parameters of flow simulation are ranking as Scs Curve Number(CN2), Soil evaporation compensation coefficient(ESCO), Delay time for aquifer recharge(GW-DELAY), Maximum amount of water that can be trapped in the canopy(CANMX), Baseflow recession constant(ALPHA-BF), Revap coefficient(GW-REVAP), Saturated hydraulic conductivity(SOL_K), Soil available water capacity(SOL_AWC), Manning’s n value for the main channel(CH_N2), Moist bulk density(SOL_BD), Bank flow recession constant or constant of proportionality(ALPHA_BNK), Effective hydraulic conductivity of channel(CH_K2). The determination coefficient R2, Nash efficiency coefficient(Ens) and the Percentage Bias(PBIAS) for calibration and validation period are 0.79, 0.78, 5.36 and 0.70, 0.58,-0.61, which indicates that model is applicable to the study area. Model uncertainty mainly comes from conceptual model uncertainty, input uncertainty and parameter uncertainty.(4)Determination of Critical Source Area of(CSA) of non-point source(NPS) pollutionThe calibrated SWAT model was used to determine CSA of NPS pollution both on subbasin scale and HRU scale.The results showed that the spatial heterogeneities of surface runoff and the total runoff in subbasin scale and HRU scale are both small, the determination of CSA of surface runoff and total flow are difficult. The spatial heterogeneities of sediment yield, total nitrogen(TN) and total phosphorus(TP) in subbasin scale and HRU scale are larger than that of surface runoff and the total runoff. Sediment, TN and TP output in small area accounted for a significant proportion of the corresponding output of the whole basin. It is easy to accurately find out the corresponding CSA. The spatial heterogeneity of sediment, TN and TP output in HRU scale is far higher than that of the corresponding output on subbasin scale, the determination of CSA is easy. So the CSA in HRU scale is more representative, the control of pollutants output have specific aim, which can greatly reduce the input of pollutant control. Problems will occur in the implementation of prevention and control of CSA, one is the HRU are too fragmented and the area is small which is not suitable for large-scale prevention, the second is the positioning of CAS in HRU scale is difficult.In order to improve the level of prevention and control of pollutants, the determination of CSA need comprehensive considerations, the area that all pollutant discharge are high should be determined as the CSA.(5)Evaluation of the impact of Grain for Green practice on the output of NPS pollutionBest management practices are divided into structural and non-structural practices, Grain for Green practice as a non-structural measures, understanding of its effect on non-point source pollution prevention and control can provide a reference for the implementation of the policy. Keep the setup and parameters of calibrated model unchanged, the landuse type AGRL was modified to FRSE to simulate the impact of grain for grenn measures on the output of NPS pollution. The results showed that after the implementation of grain for green, the total flow in the watershed outlet did not decrease, inversely increased a little. This may be caused by model system error or the error of the calibration process. The mineral phosphorus also increased slightly, this indicated that the output of mineral phosphorus in woodland is bigger than the output of farmland. Sediment, organic nitrogen and organic phosphorus, nitrate nitrogen, ammonium nitrogen in the basin outlet sharply reduced, and the sediment and nitrate reduction ratio was more than 50%, this shows that sediment, organic nitrogen, organic phosphorus, nitrate nitrogen and ammonium nitrogen in the NPS pollution mainly comes from farmland. The grain for green practice is satisfactory measures to reduce the output of NPS pollution.