Gao Xiao-Xi, Zuo De-Peng, Ma Guang-Wen, Xu Zong-Xue, Hu Xiao-Hong, Li Pei-Jun
Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, College of Water Sciences, Beijing Normal University, Beijing 100875, China.
State Environment Protection Key Laboratory of Environmental Monitoring Quality Control, China National Environmental Monitoring Centre, Beijing 100012, China.
Huan Jing Ke Xue. 2020 Oct 8;41(10):4564-4571. doi: 10.13227/j.hjkx.202002036.
Aiming at non-point sources pollution in the agricultural areas with large topographic fluctuations and spatial differences in precipitation, a SWAT model was used to evaluate the spatial variations in the critical source areas (CSAs) of total nitrogen (TN) and total phosphorus (TP) under two precipitation scenarios, i.e., heterogeneous precipitation and uniform precipitation. A change in the CSAs identified based on the two precipitation scenarios during the study period were statistically calculated, and the relationship between the CSAs and precipitation variables was discussed. The study results showed that when the total precipitation was the same, the variation tendency of the identified CSAs for TN and TP under the two precipitation scenarios were similar, and very close for a few years. According to the results of the pair test, the CSAs of TP were not affected by the spatial variation of precipitation, while the change in CSAs for TN was more significant under different precipitation scenarios, which is likely due to the difference in the physical properties of nitrogen and phosphorus. The correlation analysis between the CSAs of TN and TP with precipitation variables showed that the variation in the CSAs of TP was positively correlated with the precipitation variables in the same year, while the variation in the CSAs of TN was strongly related to the precipitation variables of the previous year. The results obtained in this study are of great significance for further exploring the impact of uncertainty of precipitation, which is an important driving factor, on the CSAs of non-point sources pollution and the governance of agricultural non-point sources pollution.
针对地形起伏大、降水存在空间差异的农业面源污染问题，采用SWAT模型评估了两种降水情景下（即非均匀降水和均匀降水）总氮（TN）和总磷（TP）关键源区（CSA）的空间变化。统计计算了研究期间基于两种降水情景识别出的CSA的变化情况，并探讨了CSA与降水变量之间的关系。研究结果表明，当总降水量相同时，两种降水情景下识别出的TN和TP的CSA变化趋势相似，且有几年非常接近。根据配对检验结果，TP的CSA不受降水空间变化的影响，而不同降水情景下TN的CSA变化更为显著，这可能是由于氮和磷物理性质的差异所致。TN和TP的CSA与降水变量的相关分析表明，TP的CSA变化与同年降水变量呈正相关，而TN的CSA变化与上一年降水变量密切相关。本研究所得结果对于进一步探究作为重要驱动因素的降水不确定性对非点源污染关键源区及农业面源污染治理的影响具有重要意义。
