Study Of Non-point Source Pollution In Yuecheng Reservoir Basin And A New Approach To Identify The Critical Source Pollution Areas

SWAT(Soil and Water Assessment Tool) model was used to simulate the non-point source pollution in Yue-cheng reservoir basin. A more realistic non-point source pollution model was established based on the pollution sources data gained through field survey and yearbook statistics. Monthly simulated results of flow, sediment, TN and TP were compared with the corresponding observed data at three stations(Shiliang, liujiazhuang and Guaitai station) for the period from 2006 to 2009, which shows the performance of SWAT model was acceptable. The SWAT model can be well used in the study of non-point source pollution and the identification of critical source areas in Yue-cheng reservoir basin.This study has found that the average non-point source contribution was less than 50%, and the average annual TN and TP loadings were 3,025 t and 234 t respectively. Among the pollution sources, point source pollution of TN was mainly from industrial sewage with the contribution of 31.9%, and TP was mainly from urban sewage with the contribution of 36%; non-point source pollution was mainly from agricultural fertilizer, livestock waste and rural domestic wastewater with the contributions of 16.9%, 10.5% and 2.6% respectively. Agriculture area was the dominant land-use of non-point source pollution. Average annual TN and TP loadings per unit area were 2.77kg/hm2 and 0.397kg/hm2 respectively.Critical source areas(CSAs) are the areas that are relatively more erosion-prone and contribute significantly more pollutants per unit area. They have been widely recognized as optimal locations for the control of non-point source pollution. SWAT model has been frequently used to identify the CSAs of non-point source pollution on a basin scale. In previous studies, CSAs were identified based on the simulated average annual nutrient yields for the simulation period at the levels of sub-basin or hydrologic response unit(HRU). However, this method did not consider the impact of uneven spatial distribution of precipitation, which is considered to be the driven force of non-point source pollution. In many cases, due to limited length of qualified monitoring data collected, the simulation period may not cover a full spectrum of the precipitation characteristics so that some potential CSAs may be missed. In the present study, the precipitation driven correlation based mapping method(PCM) was proposed, which can reduce the impact of uncertain spatial-temporal distribution of precipitation and identify the critical source areas of non-point source pollution with a better coverage. PCM was applied to Yue-cheng reservoir basin for the identification of CSAs. Identification results were analysied and compared with that of previous method to disscuss the feasibility and rationality of PCM method, which shows that the proposed PCM method may reduce the impact of uncertain spatial-temporal distribution of precipitation and can provide a better coverage of the potential CSAs than the previous used method, especially when qualified monitoring data is limited and the simulation period is too short to cover the full spectrum of rainfall events.