Estimation of non-point source pollution load in Tumenxigou watershed of Miyun Reservoir

Water quality of Miyuan Reservoir affects water quality of the surface drinking water sources in Beijing. At present, non-point source pollution is a major contributor to water quality decline in Miyuan Reservoir with the point source pollution efficiently controlled. To meet the needs of the water resources protection, six runoff plots with different soil and water conservation measures were chosen in Tumenxigou small watershed of the reservoir basin, namely, chestnut (Castanea mollissima Bl.) economic forest, Chinese pine (Pinus tabulaeformis Carr.) plantation, Chinese pine (Pinus tabulaeformis Carr. ) and blacklocust (Robinia pseudoacacia Linn.) mixed forest, shrub (Vitex negundo Linn. var. heterophylla Rehd.), and maize agriculture land, then pollutant concentration and overland discharge under runoff generating rainfall events were monitored in 2007. Non-point source pollution load and spatial distribution of soil erosion within the watershed were estimated and mapped by using RUSLE and SCS method integrated with ArcGIS tools. The results showed that non-point source pollution was mainly generated by soil erosion with pollutant absorbed in the soil particles. Of all different soil and water conservation measures, the order pollutant load per unit area is economic forest>broadleaf forest>shrub>coniferous forest>mixed forest and farmland. Therefore, land use planning in this region to control soil erosion should be developed by reducing economic forest, increasing broadleaf and coniferous mixed forest, sustaining existing terrace field, forbidding growing crops on steep slopes, adopting terrace mode at the slope toe and channel system in order to control the non-point source pollution. In contrast with the general conclusion drawn by other similar research, the non-point source pollution of the farmland is lesser than woodland due to large infiltration capacity (small overland flow contribution) and organic fertilizer applied for growing crops.