区域尺度黄河流域面源污染负荷特征与来源解析

张志杰; 温飞; 张亚群; 周静; 冯爱萍

doi:10.13205/j.hjgc.202209011

区域尺度黄河流域面源污染负荷特征与来源解析

doi: 10.13205/j.hjgc.202209011

1. 甘肃省生态环境科学设计研究院, 兰州 730000;
2. 生态环境部卫星环境应用中心, 北京 100094

基金项目:

甘肃省自然科学基金(20JR10RA442)

详细信息

作者简介:
张志杰(1993-),男,硕士,助理工程师,主要研究方向为流域水环境。zzj2154@126.com

通讯作者:
张亚群(1972-),女,博士,正高级工程师,主要研究方向为流域水环境污染及环境健康。840819476@qq.com

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- 被引次数: 0
出版历程
- 收稿日期: 2021-11-30
- 网络出版日期: 2022-11-09

CHARACTERISTICS AND SOURCE ANALYSIS OF NON-POINT SOURCE POLLUTION LOAD IN THE YELLOW RIVER BASIN ON A REGIONAL SCALE

1. Gansu Academy of Eco-environmental Sciences, Lanzhou 730000, China;
2. Satellite Application Center for Ecology and Environment, MEE, Beijing 100094, China

摘要

摘要: 掌握黄河流域甘肃段面源污染负荷特征及其来源,是在区域尺度上提升水环境污染治理水平的重要基础。基于DPeRS面源模型,从农田径流、城镇径流、畜禽养殖、农村生活、水土流失5大污染类型,选取TN、TP、NH₃-N和COD 4个污染指标,对甘肃黄河流域9个市(州)58个县(区)面源污染进行污染负荷估算、污染来源解析及空间分布分析。结果表明:从模型估算结果看,2018年整个流域TN、TP、NH₃-N和COD面源污染排放负荷均值分别为65.6,11.8,19.1,77.2 kg/km²。从区域尺度分析,甘肃黄河流域TN、TP面源污染负荷最高的区域均是兰州市安宁区,分别占整个流域总负荷的10.83%和5.16%;NH₃-N和COD面源污染负荷最高的区域均是临夏回族自治州临夏市,分别占整个流域总负荷的26.23%和56.56%。从污染产生来源分析,TN、TP、NH₃-N和COD的首要污染来源分别为农田径流、水土流失、农田径流和畜禽养殖。从空间分布分析,黄河流域各县(区)面源污染总负荷呈中间高两边低的分布特征,污染负荷较重的区域主要集中在黄河兰州段、大夏河临夏段、渭河天水段等局部区域。
- 黄河流域 /
- 面源污染 /
- DPeRS模型 /
- 来源解析 /
- 污染负荷特征
Abstract: Grasping the characteristics and sources of non-point source pollution load in the Gansu section of the Yellow River Basin is an important basis for improving the level of water pollution control on a regional scale. Based on the DPeRS model, this study selected four pollution indicators of total nitrogen, total phosphorus, ammonia nitrogen and chemical oxygen demand, from the five major pollution types, farmland runoff, urban runoff, livestock and poultry breeding, rural life, and soil erosion. Pollution load estimation, pollution source analysis and spatial distribution analysis were carried out on non-point source pollution of nine cities(prefectures) and 58 districts(counties). The results showed that: from the model estimation results, the average non-point source pollution load of total nitrogen, total phosphorus, ammonia nitrogen and chemical oxygen demand in the entire basin in 2018 was 65.6,11.8,19.1, 77.2 kg/km². From the regional scale analysis, the area with the highest non-point source pollution load of total nitrogen and total phosphorus in the Yellow River Basin of Gansu was Anning District, Lanzhou, which accounted for 10.83% and 5.16% of the total load of the entire basin respectively; the area with the highest non-point source pollution load of ammonia nitrogen and chemical oxygen demand was Linxia City in Linxia Prefecture, respectively, accounted for 26.23% and 56.56% of the total load of the entire basin. From the analysis of pollution sources, the primary pollution sources of total nitrogen, total phosphorus, ammonia nitrogen and chemical oxygen demand were farmland runoff, soil erosion, farmland runoff, and livestock and poultry farming. From the spatial distribution analysis, the total non-point source pollution load of each district(county) of the Yellow River Basin presented a distribution characteristic of middle-high and low sides. The areas with heavier pollution load were mainly concentrated in local areas such as the Lanzhou section of the Yellow River, the Linxia section of the Daxia River, and the Tianshui section of the Weihe River.
- Yellow River Basin /
- non-point source pollution /
- DPeRS model /
- source analysis /
- pollution load characteristic

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参考文献(19)

[1]	杨奇奇,靳峰,张富,等.甘肃黄河流域生态环境现状及防治对策[J].中国水土保持,2021(4):26-30.
[2]	李家科,彭凯,郝改瑞,等.黄河流域非点源污染负荷定量化与控制研究进展[J].水资源保护,2021,37(1):90-102.
[3]	梁冬梅.小流域面源污染特征与控制技术研究[D].长春:吉林大学,2014.
[4]	高康宁.兰州段黄河流域农业面源污染分析研究[D].兰州:兰州大学,2009.
[5]	华维霞.2007—2012年黄河兰州段农业非点源污染研究[D].西安:西北师范大学,2015.
[6]	刘全諹,齐明亮,马啸宙,等.基于遥感和GIS的洮河流域面源污染流域尺度模拟及防治对策研究[J].干旱区地理,2020,43(3):706-714.
[7]	康启燕.祖厉河流域农业面源污染特征研究[D].兰州:甘肃农业大学,2016.
[8]	任艺彬,巨天珍,卢造权,等.庆阳市马莲河、蒲河流域总氮总磷污染特征及其控制策略[J].湖北农业科学,2016,55(17):4460-4464.
[9]	韩柳.湟水流域面源污染负荷分析与模拟研究[D].西安:长安大学,2020.
[10]	LI H Z,ZHANG M X. A review on the calculation of non-point source pollution loads[J]. IOP Conference Series Earth and Environmental Science,2019,344:012138.
[11]	冯爱萍,王雪蕾,徐逸,等.基于DPeRS模型的海河流域面源污染潜在风险评估[J].环境科学,2020,41(10):4555-4563.
[12]	杨艳春,闫莉,程伟.黄河流域非点源污染估算研究[J].人民黄河,2011,33(11):66-68.
[13]	HENRI C V, HARTER T, DIAMANTOPOULOS E. On the conceptual complexity of non-point source management:impact of spatial variability[J]. Hydrology and Earth System Sciences,2020,24(3):1189-1209.
[14]	WANG X L,WANG Q,WU C Q,et al. A method coupled with remote sensing data to evaluate non-point source pollution in theXin’anjiang catchment of China[J]. Science of the Total Environment,2012,430:132-143.
[15]	王谦,冯爱萍,于学谦,等.DPeRS模型在重点流域面源污染优控单元划分中的应用:以吉林省为例[J].环境与可持续发展,2016,41(4):111-115.
[16]	殷守敬,吴传庆,王晨,等.综合遥感与地面观测的巢湖水体富营养化评价[J].中国环境监测,2018,34(1):157-164.
[17]	JOY T A,MUTHUKRISHNA V K. Assessing non-point source pollution models:a review[J]. Polish Journal of Environmental Studies,2018,27(5):1913-1922.
[18]	WU B F. Watershed remote sensing:methodology and a paradigm in Hai Basin[J]. Journal of Remote Sensing,2011,15(2):201-223.
[19]	王雪蕾,王新新,朱利,等.巢湖流域氮磷面源污染与水华空间分布遥感解析[J].中国环境科学,2015,35(5):1511-1519.