Analyzing “Source-Sink” Pattern of NPS Pollution Risks in Upper Reaches of Erhai Lake Basin by Minimum Cumulative Resistance Model

Dong Yakun; Wang Yu; Zeng Weijun

doi:10.13961/j.cnki.stbctb.2022.06.021

您当前的位置：

首页 >

文章列表页 >

Analyzing “Source-Sink” Pattern of NPS Pollution Risks in Upper Reaches of Erhai Lake Basin by Minimum Cumulative Resistance Model

- Analyzing “Source-Sink” Pattern of NPS Pollution Risks in Upper Reaches of Erhai Lake Basin by Minimum Cumulative Resistance Model
- Bulletin of Soiland Water Conservation Vol. 42, Issue 6, Pages: 166-175(2022)
- 作者机构：
  
  1. 云南农业大学水利学院,云南,昆明,650201
  2. 自然资源部云南山间盆地土地利用野外科学观测研究站,云南,昆明,650201
  3. 云南省土地资源利用与保护工程实验室,云南,昆明,650201
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2022.06.021
  CLC： X87;X522
- Published：2022
- 稿件说明：
移动端阅览
Dong Yakun, Wang Yu, Zeng Weijun. Analyzing “Source-Sink” Pattern of NPS Pollution Risks in Upper Reaches of Erhai Lake Basin by Minimum Cumulative Resistance Model[J]. Bulletin of Soiland Water Conservation, 2022, 42(6): 166-175.
DOI：

Dong Yakun, Wang Yu, Zeng Weijun. Analyzing “Source-Sink” Pattern of NPS Pollution Risks in Upper Reaches of Erhai Lake Basin by Minimum Cumulative Resistance Model[J]. Bulletin of Soiland Water Conservation, 2022, 42(6): 166-175. DOI： 10.13961/j.cnki.stbctb.2022.06.021.

摘要

[目的

]

对洱海流域上游面源污染“源-汇”风险格局进行研究，为保护洱海生态和快速识别面源污染“源-汇”风险的关键区域提供理论依据。 [方法

]

以2005，2010，2015和2020年数据为例，构建阻力基面评价体系，基于最小累积阻力模型建立阻力面，划分面源污染风险等级并探讨洱海流域上游16 a来面源污染的风险等级变化。 [结果

]

①阻力因子的空间异质性使阻力基面的分布存在区域性差异，而“源”的分布则影响阻力面的分布，2020年比2005年阻力面值提高了7 485.40。 ②研究区极高风险区面积所占比例达30%，而中风险区以上所占比例超过60%，面源污染风险等级偏高；16 a间，极高风险区面积减少最多，为35.74 km

，而中风险区面积增加最多，为38.69 km

。 ③面源污染风险等级距离“源”越近，风险等级越高，表现为中部高于边界，南部高于北部，而极高风险区是面源污染的关键区域。 ④16 a间中风险区转出面积最多，为80.93 km

。茈碧湖镇、凤羽镇和右所镇三镇交界处以及牛街乡的北部是面源污染风险等级转移的主要区域。 [结论

]

关键区域的景观优化、种植业调整等措施对减少氮磷的流失及风险等级格局的改变具有更积极的作用，可进一步改善洱海未来水环境。

Abstract

[Objective] The “source-sink” risk pattern of non-point source (NPS) pollution in the upper reaches of the Erhai Lake basin was identified in order to provide a theoretical basis for protecting the ecology of Erhai Lake and for rapidly identificatiing key areas of “source-sink” NPS pollution risk. [Methods] An evaluation system of resistance base surfaces was built based on data from 2005

2010

2015

and 2020. Resistance surfaces were established and NPS pollution risk levels were classified based on the minimum cumulative resistance model to analyze changes in NPS pollution risk levels over these 16 years in the upper reaches of the Erhai Lake basin. [Results] ① Spatial heterogeneity in the resistance factor caused regional differences in the distribution of the resistance base surfaces

while the distribution of the “source” affected the distribution of the resistance surfaces. The resistance surfaces value increased by 7 485.40 from 2005 to 2020. ② Thirty percent of the study area was classified as extremely high-risk zones

while the area of the medium-risk zones accounted for more than 60% of the study area

and the NPS pollution risk level was high. During the 16 years of the study

the area of extremely high-risk zones decreased the most (35.74 km2)

while the area of medium-risk zones increased the most (38.69 km2). ③ The closer the NPS pollution risk level was to the “source”

the higher the risk level. The risk level was higher in the central region than at the border

and higher in the south than in the north

while the extremely high-risk zones were the key area of NPS pollution. ④ Among zones of different risk levels

the medium-risk zones witnessed the largest transfer-out (80.93 km2) in the past 16 years. The main transfer-out areas were the intersections of three towns (Cibi Lake

Fengyu

and Yousuo) and the northern part of Niujie Town. [Conclusion] Measures such as landscape optimization and planting adjustments in key zones have a more positive effect on reducing the loss of nitrogen and phosphorus and changing the risk level pattern

which could further improve the future water environment of the Erhai Lake.

关键词

Keywords

references

陈虹,郭兆成,贺鹏.1988-2018年洱海流域植被覆盖度时空变换特征探究[J].国土资源遥感,2021,33(2):116-123.

项颂,万玲,庞燕.土地利用驱动下洱海流域入湖河流水质时空分布规律[J].农业环境科学学报,2020,39(1):160-170.

Zheng Liang, An Zeyu, Chen Xiaoling, et al. Changes in water environment in Erhai lake and its influencing factors[J]. Water, 2021,13(10):1362-1378.

Liu Yiwen, Li Jiake, Xia Jun, et al. Risk assessment of non-point source pollution based on landscape pattern in the Hanjiang River basin, China[J]. Environmental Science and Pollution Research, 2021,28(45):64322-64336.

Zhu Kangwen, Chen Yucheng, Zhang Sheng, et al. Identification and prevention of agricultural non-point source pollution risk based on the minimum cumulative resistance model[J]. Global Ecology and Conservation, 2020, 23:e01149.

严春丽,赵明,李泽坤,等.洱海北部入湖河流水质特征及其对北部湖区的影响[J].环境工程,2020,38(12):59-63.

姜海斌,沈仕洲,谷艳茹,等.洱海流域不同施肥模式对稻田氮磷径流流失的影响[J].农业环境科学学报,2021,40(6):1305-1313.

沈仕洲,杨艳,王瑞琦,等.施肥对云南洱海流域蒜田土壤氨挥发和大蒜产量的影响[J].植物营养与肥料学报,2021,27(3):470-479.

Wang Jinliang, Shao Jiuan, Wang Dan, et al. Identification of the "source" and "sink" patterns influencing non-point source pollution in the Three Gorges Reservoir Area[J]. Journal of Geographical Sciences, 2016, 26(10):1431-1448.

Wuyi Jiang, Yongli Cai, Jingjing Tian. The application of minimum cumulative resistance model in the evaluation of urban ecological land use efficiency[J]. Arabian Journal of Geosciences, 2019,12(23):714-720.

谭华清,张金亭,周希胜.基于最小累计阻力模型的南京市生态安全格局构建[J].水土保持通报,2020,40(3):282-288.

许芬,周小成,孟庆岩,等.基于"源-汇"景观的饮用水源地非点源污染风险遥感识别与评价[J].生态学报,2020,40(8):2609-2620.

Zhou Zixiang, Li Jing. The correlation analysis on the landscape pattern index and hydrological processes in the Yanhe watershed, China[J]. Journal of Hydrology, 2015,524(5):417-426.

Zhang Xin, Zhou Lin, Liu Yuqi. Modeling land use changes and their impacts on non-point source pollution in a Southeast China coastal watershed[J]. International Journal of Environmental Research and Public Health, 2018,15(8):1593-1607.

王金亮,谢德体,邵景安,等.基于最小累积阻力模型的三峡库区耕地面源污染源-汇风险识别[J].农业工程学报,2016,32(16):206-215.

刘帆,谢德体,王三.基于最小累积阻力模型的耕地面源污染源-汇风险格局评价:以重庆市北碚区为例[J].江苏农业科学,2018,46(14):253-259.

陈昕,彭建,刘焱序,等.基于"重要性-敏感性-连通性"框架的云浮市生态安全格局构建[J].地理研究,2017,36(3):471-484.

Chuan Limin, Zheng Huaiguo, Wang Ailing, et al. The situation and research progress of agricultural non-point source pollution in China[J]. Iop Conference Series:Earth and Environmental Science, 2020,526(1):012015.

Jeyrani F, Morid S, Srinivasan R. Assessing basin blue-green available water components under different management and climate scenarios using SWAT[J]. Agricultural Water Management, 2021,256:107074.

郝守宁,白庆芹,张志伟,等.林芝市农业面源污染排放特征解析[J].灌溉排水学报,2018,37(8):115-120.

武升,张俊森,张东红,等.小流域农业面源污染评价与综合治理研究进展[J].环境污染与防治,2018,40(6):710-716.

Zheng Guihua, Cui Xiong, Li Shiyao, et al. Research on non-point source pollution and prevention countermeasures of river basin based on remote sensing and GIS[J]. Arabian Journal of Geosciences, 2021,14(6):1-14.

贾玉雪,帅红,韩龙飞.基于"源-汇"理论的资江下游地区非点源污染风险区划[J].应用生态学报,2020,31(10):3518-3528.

尹发能,王学雷.基于最小累计阻力模型的四湖流域景观生态规划研究[J].华中农业大学学报,2010,29(2):231-235.

陈裕婵,张正栋,万露文,等.五华河流域非点源污染风险区和风险路径识别[J].地理学报,2018,73(9):157-169.

熊星,唐晓岚,叶海跃,等.基于"源汇"格局的传统乡村景观保护与导控策略[J].地域研究与开发,2019,38(6):120-125.

Huang Ning, Lin Tao, Guan Junjie, et al. Identification and regulation of critical source areas of non-point source pollution in medium and small watersheds based on source-sink theory[J]. Land, 2021,10(7):668-668.

Li Feng, Ye Yaping, Song Bowen, et al. Evaluation of urban suitable ecological land based on the minimum cumulative resistance model:A case study from Changzhou, China[J]. Ecological Modelling, 2015,318(1):194-203.

汉瑞英,赵志平,肖能文,等.基于"源-汇"理论和生态阻力面(UEER)模型的新疆和田地区沙源扩散路径[J].地球科学与环境学报,2020,42(5):701-710.

Wang Jinliang,Ni Jiupai,Chen Chenglong, et al. Source-sink landscape spatial characteristics and effect on non-point source pollution in a small catchment of the Three Gorge Reservoir Region[J]. Journal of Mountain Science, 2018,15(2):327-339.

Razavi Termeh Seyed Vahid, Sadeghi Niaraki Abolghasem, Choi Soo Mi. Gully erosion susceptibility mapping using artificial intelligence and statistical models[J]. Geomatics Natural Hazards and Risk, 2020, 11(1):821-844.

杨子生.云南省金沙江流域土壤流失方程研究[J].山地学报,2002,20(S1):1-9.

Jiang Luguang, Liu Ye, Wu Si, et al. Analyzing ecological environment change and associated driving factors in China based on NDVI time series data[J]. Ecological Indicators, 2021,129:107933.

Song Ge, Zhang Hongmei. Cultivated land use layout adjustment based on crop planting suitability:A case study of typical counties in Northeast China[J]. Land, 2021,10(2):107-125.

王琦,魏来,韩煜,等.查干湖汇水区面源污染风险识别及管控[J].环境科学研究,2020,33(9):2074-2083.

徐建锋,贾海燕,辛小康.基于最小累积阻力模型的丹江口水源区面源污染风险识别[C]//.中国水利学会2020学术年会论文集(第一分册),2020:335-340. DOI:10,26914/c. cnkihy.2020.069744.

孔佩儒,陈利顶,孙然好,等.海河流域面源污染风险格局识别与模拟优化[J].生态学报,2018,38(12):4445-4453.

Views

544

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Changes and its driving factors of ecological environment quality in Yellow River Source Park from 2000 to 2024

Spatiotemporal variation characteristics of different grade precipitation in Jilin Province from 1960 to 2024

Soil-water characteristics and softening constitutive model of lime-stabilized loess

Influence of vegetation blanket coverage on thermal properties of coal gangue substrate in alpine mining areas

Effectiveness evaluation of ecological product value realization in northwest China——An analysis of 29 typical cases

Related Author

No data

Related Institution

No data

⁰