| 降水空间异质性对非点源关键源区识别面积变化的影响 |
| 摘要点击 1483 全文点击 526 投稿时间：2020-02-06 修订日期：2020-04-10 |
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| 中文关键词 非点源污染 关键源区(CSAs) 降水空间异质性 SWAT模型 总氮(TN) 总磷(TP) |
| 英文关键词 non-point sources pollution critical source areas (CSAs) spatial heterogeneity of precipitation SWAT model total nitrogen (TN) total phosphorus (TP) |
| 作者 | 单位 | E-mail | | 高晓曦 | 北京师范大学水科学研究院, 城市水循环与海绵城市技术北京市重点实验室, 北京 100875 | xxgao@mail.bnu.edu.cn | | 左德鹏 | 北京师范大学水科学研究院, 城市水循环与海绵城市技术北京市重点实验室, 北京 100875 | dpzuo@bnu.edu.cn | | 马广文 | 中国环境监测总站, 国家环境保护环境监测质量控制重点实验室, 北京 100012 | | | 徐宗学 | 北京师范大学水科学研究院, 城市水循环与海绵城市技术北京市重点实验室, 北京 100875 | | | 胡小红 | 北京师范大学水科学研究院, 城市水循环与海绵城市技术北京市重点实验室, 北京 100875 | | | 李佩君 | 北京师范大学水科学研究院, 城市水循环与海绵城市技术北京市重点实验室, 北京 100875 | |
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| 中文摘要 |
| 针对地形起伏和降水空间差异较大的农业区非点源污染问题，基于SWAT模型评估了阿什河流域在异质性降水和均匀降水两种情景下总氮、总磷关键源区空间变化规律，统计了两种情景下识别的关键源区面积变化，并分析其与降水特征参数的关系.结果表明，降水量一定时，两种情景下识别的总氮、总磷关键源区面积变化趋势大致相同，且总磷关键源区面积不易受降水空间异质性的影响，但总氮关键源区面积却明显受到其影响.对各年份总氮和总磷关键源区面积与降水特征参数的相关分析表明，总磷关键源区面积与当年降水量呈显著正相关，而总氮关键源区面积却与前一年降水量呈显著正相关.研究结果对进一步探讨降水这一重要驱动因子的不确定性对非点源污染关键源区的影响，以及农业非点源污染的治理具有重要意义. |
| 英文摘要 |
| 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 t 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. |
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