太湖流域浙西区不同土地类型的面源污染产出

The Non-point Output of Different Landuse Typesin Zhexi Hydraulic Region of Taihu Basin

以太湖流域浙西水利分区为研究区,采用Arcgis的水文分析模块,对浙西区进行流域划分,选取以单一农业用地为主的子流域,利用GIS叠加分析方法,获取各子流域的降水、径流深度、土地利用结构信息,分析研究区主要土地利用类型与径流量的统计关系,建立该区年尺度的径流估算模型。基于林地、耕地为主的子流域水质监测数据,结合径流估算模型,分析占该区90%土地利用面积的林地、耕地与径流污染物浓度的定量关系,研究结果显示,该研究区以林地为主的流域径流各水环境指标为:COD浓度为2.95 mg/l,BOD浓度为1.080 mg/l,总氮浓度为0.715 mg/l,总磷浓度为0.039 mg/l;耕地为主的流域径流水环境指标为:COD浓度为5.721mg/l,BOD浓度为3.097 mg/l,总氮浓度为2.092 mg/l,总磷浓度为0.166 mg/l。这一研究结果适合应用于太湖流域上游山区、丘陵地区年尺度面源污染估算。

This paper takes Zhexi hydraulic region in Taihu Basin as the study area. Using hydraulic analysis function of Arcgis8.3, the drainages were delineated by selecting the monitoring points and discharge stations as outlets. The landuse map was finished by denoting the TM/ETM image. The precipitation map was finished by spatial interpolation using the rainfall monitoring records. Overlaying the drainage boundary, landuse map and precipitation map, the rainfall, areas of different landuse types, and runoff pollution concentration and runoff were calculated. Based on these data in different drainages, by Origion7.0 regression tool, an equation is found to predict runoff using the relationship between runoff, precipitation depth and percentage of land use in each of the drainages. Selecting the sub-watershed which is mainly composed of forest landuse type, the mean runoff concentration (MRC) from sub-watershed has been estimated. The mean runoff concentration of farmland has been estimated by the same methods after removing the contribution of forest landuse type. The result is: for the forest landuse type, the mean runoff concentrations of COD, BOD, Total N and Total P are 2.95 mg/l, 1.080 mg/l, 0.715 mg/l, and 0.039 mg/l; for the farmland, the mean runoff concentrations of COD, BOD, Total N and Total P are 5.721 mg/l, 3.097 mg/l 2.092 mg/l, and 0.166 mg/l. Using these results, the agricultural non-point pollution loads have been assessed. The loads of COD, BOD, Total N and Total P in Zhexi region are 14631.69 t/a, 6401.93 t/a, 4281.753 t/a and 287.67 t/a respectively.