季冻区农药化肥施用的湖泊富营养化响应

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Abstract To investigate the eutrophication and driving factors of lakes in the frozen region of northern China, the study takes Lake Chagan in western Jilin Province as the research object. Based on monitoring data, the Back Propagation (BP) neural network has been systematically applied to evaluate the eutrophication of lake and the excess nutrient indicators have been identified to analyze their dynamic characteristics. After that, the EQC model has been used to simulate the influence of water from pesticide and fertilizer residues in irrigation drainage and explore the drivers of the lake eutrophication. The results showed that: During 2016~2019, the lake was generally mildly eutrophic, with the main excess nutrient indicators being COD_Mn, COD_Cr, TP and TN, etc. The concentration of COD_Mn, COD_Cr and TP were driven by low temperatures and showed an increasing trend during the freezing period, among them, the concentration of TP increased 10%, approximately. Meanwhile, the concentration of TP and TN, were driven by irrigation and drainage that showed an upward trend during the receding irrigation period. Through EQC simulation, the contribution values of TN and TP concentrations of irrigation area drainage into the lake were obtained as 2.717mg/L and 0.080mg/L, respectively. The residual pesticide and fertilizer from the irrigation drainage were the main factors driving the increase of the TN content in the lake during the receding period, with a maximum rise of 27%. Low temperatures were the main driver of the increase of the TP content in the lake during the freeze-up period (maximum increase of about 10%). Meanwhile, the application of pesticides and fertilizers in spring has led to a trend of increased eutrophication in the lakes of the seasonal freeze region during the winter and summer. In conclusion, the management of lake eutrophication still needs to focus on reducing exogenous pollution, especially fertilizer pollution, during the receding period of the irrigation area.

Key words： irrigation drainage pesticides and fertilizers seasonal frozen region lake eutrophication multi-media model BP Neural Networks

Received: 07 November 2022

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X524

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	Articles by authors
	LOU Yu-qi
	BIAN Jian-min
	SUN Xiao-qing
	WANG Yu
	WANG Fan
	LI Mu-rong

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LOU Yu-qi,BIAN Jian-min,SUN Xiao-qing等. Investigation on lake eutrophication response to pesticide and fertilizer application in the seasonal freeze region[J]. CHINA ENVIRONMENTAL SCIENCECE, 2023, 43(S1): 301-308.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2023/V43/IS1/301

[1] 杨文焕,冯栋栋,杨芳,等.冰封期湖泊溶解氧变化特征及代谢速率[J].湖泊科学, 2022,34(6):2156-2168. Yang W H, Feng D D, Yang F, et al. Variation characteristics of dissolved oxygen and metabolic rate in lakes during the ice-covered period [J].China Environmental Science, 2022,34(6):21156-2168.
[2] Smith V H, Schindler D W. Eutrophication science: Where do we go from here? [J] Trends in Ecology & Evolution, 2009,24(4):201–207.
[3] Schindler D W, Carpenter S R, Chapra S C, et al. Reducing Phosphorus to Curb Lake Eutrophication is a Success [J].Environmental Science & Technology, 2016,50(17):8923-8929.
[4] Conley D J, Paerl H W, Howarth R W, et al. Ecology controlling eutrophication: nitrogen and phosphorus [J].Science, 2009,323(5917): 1014-1015.
[5] Hamilton H A, Ivanova D, Stadler K, et al. Trade and the role of non-food commodities for global eutrophication [J].Nature Sustainability, 2018,1(6):314-321.
[6] 万杰,袁旭音,叶宏萌,等.洪泽湖不同入湖河流沉积物磷形态特征及生物有效性[J].中国环境科学, 2020,40(10):4568-4579. Wang J, Yuan X Y, Ye H M, et al. Characteristics and bioavailability of different forms of phosphorus in sediments of rivers flowing into Hongze Lake [J].China Environmental Science, 2020,40(10):4568-4579.
[7] 盛恩国,刘斌,张忠义,等.喀斯特地区供水水库营养演化历史重建[J].中国环境科学, 2020,40(12):5403-5412. Sheng E G, Liu B, Zhang Z Y, et al. Reconstruction of trophic state changes in a karst water-supply reservoir [J].China Environmental Science, 2020,40(12):5403-5412.
[8] Mackenthun K M. Eutrophication and biological associations [C]// Environmental phosphorus handbook. New York: Wiley, 1973:613-632.
[9] Liu X M, Zhang G X, Xu Y J, et al. Determining water allocation scheme to attain nutrient management objective for a large lake receiving irrigation discharge [J].Journal of Hydrology, 2021,603(PA). DOI:10.1016/j.jhydrol.2021.126900.
[10] Sharma S, Blagrave K, Magnuson J J. et al. Widespread loss of lake ice around the Northern Hemisphere in a warming world [J].Nature Climate Change, 2019,9(3). DOI:10.1038/s41558-018-0393-5.
[11] Ding T T, Du S L, Huang Z Y, et al. Water quality criteria and ecological risk assessment for ammonia in the Shaying River Basin, China [J].Ecotoxicology and Environmental Safety, 2021,215.DOI: 10.1016/j.ecoenv.2021.112141.
[12] Mng'ong'o M, Munishi L K, Blake W, et al. Towards sustainability: Threat of water quality degradation and eutrophication in Usangu agro-ecosystem Tanzania [J].Marine Pollution Bulletin, 2022,181. DOI:10.1016/j.marpolbul.2022.113909.
[13] Guo S F, Yan T Z, Zhai L M, et al. Nitrogen transport/deposition from paddy ecosystem and potential pollution risk period in Southwest China [J].Water, 2022,14(4). DOI:10.3390/w14040539.
[14] Chu X D, Wang H, Zheng F W, et al. Spatial distribution characteristics and sources of nutrients and heavy metals in the Xiujiang River of Poyang Lake Basin in the dry season [J].Water, 2021,13(12). DOI:10.3390/w13121654.
[15] Li B, Yang G S, Wan R R. Multidecadal water quality deterioration in the largest freshwater lake in China (Poyang Lake): Implications on eutrophication management [J].Environmental Pollution, 2020, 260(C). DOI:10.1016/j.envpol.2020.114033.
[16] 丁洋,赵进勇,张晶,等.松花湖水质空间差异及富营养化空间自相关分析[J].环境科学, 2021,42(5):2232-2239. Ding Y, Zhao J Y, Zhang J, et al. Spatial differences in water quality and spatial autocorrelation analysis of eutrophication in Songhua Lake [J].Environmental Science, 2021,42(5):2232-2239.
[17] 杨金凤,冯爱萍,王雪蕾,等.海河流域农业面源污染潜在风险识别方法[J].中国环境科学, 2021,41(10):4782-4791. Yang J F, Feng A P, Wang X L, et al. An identification method of potential risk for agricultural non-point source pollution in the Haihe River Basin [J].China Environmental Science, 2021,41(10):4782-4791.
[18] 李森.查干湖低温期内源磷的释放及其对富营养化的影响[D].长春:吉林大学, 2013. Li S. Internal phosphorus of Chagan Lake Release and Impact on Eutrophication in Low Temperature Period [D].Changchun: Jilin University, 2013.
[19] 赵艳茹,董建伟.吉林查干湖总磷的变化趋势及驱动机制分析[J].吉林水利, 2018,(12):1-3,8. Zhao Y R, Dong J W. Analysis of variation trend and driving mechanism of total phosphorous in Chagan Lake of Jilin Province [J].Jilin Water Resources, 2018,(12):1-3,8.
[20] 高国明,董建伟.前郭灌区退水对查干湖水质的影响[J].吉林水利, 2015,(11):5-7,10. Gao G M, Dong J W. The impact of Irrigation water recession on the water quality in Lake Chagan, Qianguo [J].Jilin Water Resources, 2015,(11):5-7,10.
[21] Xie R F, Sun D Y, Sun L, et al. Sediment record of heavy metals over the last 150 years in Northeast China: implications for regional anthropogenic activities [J].Ecotoxicology, 2021,30(7):1354-1365.
[22] Xu P, Bian J M, Wu J J, et al. Distribution of fluoride in groundwater around Chagan Lake and its risk assessment under the influence of human activities [J].Water Science & Technology Water Supply, 2020, 20(7):2441-2454.
[23] Xu P, Bian J M, Wu J J, et al. Simulation study on the migration of F-in soil around Chagan Lake, China [J].Environmental Science and Pollution Research International, 2021,28(33):45155-45167.
[24] Liu X M, Zhang G X, Sun G Z, eal. Assessment of Lake Water Quality and Eutrophication Risk in an Agricultural Irrigation Area: A Case Study of the Chagan Lake in Northeast China [J].Water, 2019, 11(11). DOI:10.3390/w11112380.
[25] 韩宇.松原灌区农业活动影响下的地下水质量及健康风险评价[D].长春:吉林大学, 2017. Han Y. The Evaluation of groundwater quality and health risk under the influence of agricultural activities in Songyuan irrigation area [D].Changchun: Jilin University, 2017.
[26] 曹若馨,张可欣,曾维华,等.基于BP神经网络的水环境承载力预警研究——以北运河为例[J].环境科学学报, 2021,41(5):2005-2017. Cao R X, Zhang K X, Zeng W H, et al. Research on the early-warning method of water environment carrying capacity based on BP neural network: A case study of Beiyunhe River Basin [J].Acta Scientiae Circumstantiae, 2021,41(5):2005-2017.
[27] 张恒德,张庭玉,李涛,等.基于BP神经网络的污染物浓度多模式集成预报[J].中国环境科学, 2018,38(4):1243-1256. Zhang H D, Zhang T Y, Li T, et al. Forecast of air quality pollutants’ concentrations based on BP neural network multi-model ensemble method [J].China Environmental Science, 2018,38(4):1243-1256.
[28] 吴磊,谢绍东.应用EQC模型评估灭蚁灵和十氯酮的环境归趋[J].环境科学研究, 2007,(5):50-56. Wu L, Xie S D. An assessment of the environmental fates of mirex and chlordecone using EQC Model [J].Research of Environmental Sciences, 2007,(5):50-56.
[29] 覃一帆,孔祥臻,李一龙,等.逸度模型在湖泊流域农药多介质归趋研究中的应用与展望[J].湖泊科学, 2020,32(4):1212-1226. Qin Y F, Kong X Z, Li Y L, et al. Application and prospects of fugacity models in the fate of pesticides in lake watershed [J].Journal of Lake Sciences, 2020,32(4):1212-1226.