院报 ›› 2024, Vol. 41 ›› Issue (4): 55-61.DOI: 10.11988/ckyyb.20221462

• 水环境与水生态 • 上一篇    下一篇

小流域面源污染负荷精细化估算与实证研究——以成都市阳化河流域为例

夏玉超1, 袁一斌2, 詹琳1, 何楚3, 夏建新1   

  1. 1.中央民族大学 生命与环境科学学院,北京 100081;
    2.成都市环境保护科学研究院 水环境研究所,成都 610072;
    3.北京市水务局 南水北调环线管理处,北京 100176
  • 收稿日期:2022-11-04 修回日期:2022-11-30 出版日期:2024-04-01 发布日期:2024-04-11
  • 通讯作者: 夏建新(1969-),男,湖北黄冈人,教授,博士后,主要从事水资源与水环境评价研究。E-mail:jxxia@vip.sina.com
  • 作者简介:夏玉超(1997-),男,广东佛山人,硕士研究生,主要从事水环境模拟与评价研究。E-mail:13821881670@163.com
  • 基金资助:
    长江生态屏障建设成都市驻点研究项目(KY2021(003))

Refined Estimation and Empirical Study of Non-point Source Pollution Load in Small Watershed:A Case Study of Yanghua River Basin, Chengdu

XIA Yu-chao1, YUAN Yi-bin2, ZHAN Lin1, HE Chu3, XIA Jian-xin1   

  1. 1. College of Life and Environmental Science,Minzu University of China,Beijing 100081,China;
    2. Water Environment Research Department,Chengdu Academy of Environmental Sciences,Chengdu 610072,China;
    3. South-to-North Water Diversion Loop Line Management Office,Beijing Water Authority,Beijing 100176,China
  • Received:2022-11-04 Revised:2022-11-30 Online:2024-04-01 Published:2024-04-11

摘要: 精准估算沱江支流阳化河小流域面源污染负荷是制定水质达标方案的基础。运用改进的输出系数法估算阳化河流域面源污染负荷总量,并基于当月降雨量占年降雨量的比例对面源污染负荷年输出总量进行月份分配,获得精细化估算数据。结果表明:2020年流域内COD污染最严重,污染负荷总量为6 042.61 t,污染负荷主要分布在转龙镇、竹篙镇、禾丰镇、云龙镇和施家镇;污染物COD、氨氮和总磷主要来源于农村分散生活面源和规模化畜禽养殖;估算得到的面源污染负荷年内月份的分配结果与实测数据比较吻合,平均误差都<10%。研究结果可为流域水环境精细化管理提供数据支持。

关键词: 面源污染估算, 负荷分配, 改进输出系数法, 阳化河流域

Abstract: Accurately estimating non-point source pollution load is crucial for developing a standard-meeting water quality plan for the Yanghua River. By employing an improved output coefficient method, we estimated the total non-point source pollution load of Yanghua River small watershed, which is a tributary of the Tuojiang River. In consideration of the proportion of monthly rainfall in annual rainfall, we can obtain the refined estimation data of monthly distribution of non-point source pollution load. Our findings indicate that COD pollution in the watershed was most severe in 2020, with a total pollution load of 6 042.61 t, primarily concentrated in Zhuanlong Town, Zhugao Town, Hefeng Town, Yunlong Town, and Shijia Town. Non-point sources such as rural dispersed areas and large-scale livestock and poultry farming contributed significantly to pollutants such as COD, ammonia nitrogen, and total phosphorus. Additionally, we successfully obtained the preliminary monthly distribution of non-point source pollution load within the year. These results demonstrated good agreement with measured data, with an average error less than 10%. Overall, our research outcomes provide essential data support for the refined management of water environment in the basin.

Key words: estimation of non-point source pollution, pollution load distribution, improved export coefficient method, Yanghua River Basin

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