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To comprehensively evaluate the reduction potential of diffuse nitrogen pollution under the field-ditch-pond system optimization, a watershed hydrological model was used to simulate the multi-scenario optimization of field ponding water level, ditch, and pond in a typical paddy field watershed. Results showed that different optimizations had different interception effects on diffuse nitrogen pollution, and that interception effects were different over distinct hydrological years. Under the optimization of field ponding water level, the total nitrogen loss from paddy fields after optimizing the drainage water level was reduced by 7.9% to 93.9% compared to conventional water level management, with the nitrogen interception effect being better in dry years than in wet years. Under ditch optimization, the reduction rate of nitrogen loss in the watershed increased from 0.8% to 26.7% after increasing the grass planting density of ditches, with the nitrogen interception effect being better in wet years than in dry years. Under pond optimization, the reduction rate of nitrogen loss in the watershed increased from 10.5% to 18.1% after increasing the catchment area of the pond, with the nitrogen interception effect being better in dry years than in wet years. Under the multi-optimization of the field-ditch-pond system, the interception effect of field ponding water level optimization on watershed nitrogen loss was better than that of pond optimization and ditch optimization. In summary, the multi-optimization of the field-ditch-pond system can effectively control the diffuse nitrogen pollution in paddy field watersheds and could promote the sustainable development of rice production.

, correspAuthors=Wei OUYANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Lian-hua LIU, Wei OUYANG, Yan BAI, Fang-hua HAO), CN=ArticleExt(id=1241057219379261694, articleId=1241057216455832537, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=基于田-沟-塘系统优化的稻作流域氮素面源污染减排潜力评估, columnId=1234106388268503686, journalTitle=中国环境科学, columnName=环境生态, runingTitle=null, highlight=null, articleAbstract=

为全面评估稻作流域田-沟-塘系统优化条件下氮素面源污染的减排潜力,利用流域水文模型对典型稻作流域开展田面水位、沟渠和水塘多环节的情景优化模拟.结果表明,不同环节优化对氮素面源污染流失的截留效果不同,且不同水文年的截留效果存在一定差异.在田面水位优化环节,提高排水水位后的稻田总氮流失量比常规水位管理可减少7.9%~93.9%,枯水年的氮截留效果优于丰水年.在沟渠优化环节,提高沟渠植草密度后的流域氮流失削减率从0.8%提高到26.7%,丰水年的氮截留效果优于枯水年.在水塘优化环节,提高汇水面积后的流域氮流失削减率从10.5%提高到18.1%,枯水年的氮截留效果优于丰水年.在田-沟-塘系统多环节优化下,田面水位优化对流域氮流失的截留效果优于水塘优化和沟渠优化.稻作流域田-沟-塘系统多环节优化可以有效控制流域氮素面源污染流失,促进水稻生产的可持续发展.

, correspAuthors=欧阳威, authorNote=null, correspAuthorsNote=
* 责任作者,教授,
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刘连华(1991-),女,山东临沂人,副研究员,博士,主要从事流域水环境过程与污染物迁移转化研究.发表论文18篇..

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刘连华(1991-),女,山东临沂人,副研究员,博士,主要从事流域水环境过程与污染物迁移转化研究.发表论文18篇..

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刘连华(1991-),女,山东临沂人,副研究员,博士,主要从事流域水环境过程与污染物迁移转化研究.发表论文18篇..

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Ecological Engineering201137:1563–1566., articleTitle=Effects of cyclic irrigation on water and nitrogen mass balances in a paddy field, refAbstract=null)], funds=[Fund(id=1241057227553960947, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, awardId=U21A2039, language=CN, fundingSource=国家自然科学基金资助项目(U21A2039), fundOrder=null, country=null), Fund(id=1241057227679789059, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, awardId=BSRF202309, language=CN, fundingSource=中央级公益性科研院所基本科研业务费专项(BSRF202309), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241057219693834519, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, xref=1., ext=[AuthorCompanyExt(id=1241057219702223128, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, companyId=1241057219693834519, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China), AuthorCompanyExt(id=1241057219710611737, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, companyId=1241057219693834519, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.中国农业科学院农业环境与可持续发展研究所,北京 100081)]), AuthorCompany(id=1241057219937104171, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, xref=2., ext=[AuthorCompanyExt(id=1241057219949687083, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, companyId=1241057219937104171, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.School of Environment, Beijing Normal University, Beijing 100875, China), AuthorCompanyExt(id=1241057219962269997, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, companyId=1241057219937104171, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.北京师范大学环境学院,北京 100875)]), AuthorCompany(id=1241057220113264955, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, xref=3., ext=[AuthorCompanyExt(id=1241057220130042174, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, companyId=1241057220113264955, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.College of Water Sciences, Beijing Normal University, Beijing 100875, China), AuthorCompanyExt(id=1241057220142625086, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, companyId=1241057220113264955, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.北京师范大学水科学研究院,北京 100875)])], figs=[ArticleFig(id=1241057223607120590, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, language=EN, label=Fig.1, caption=Land-use types of Fushui watershed(a)and typical field-ditch-pond system in the watershed(b), figureFileSmall=3Lsvml+dG3j+6S/za/m7/w==, figureFileBig=zHzOhOY5Q557/6/UoyOSXw==, tableContent=null), ArticleFig(id=1241057223728755425, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, language=CN, label=图1, caption=洑水流域土地利用分布(a)及流域内典型田沟塘系统(b), figureFileSmall=3Lsvml+dG3j+6S/za/m7/w==, figureFileBig=zHzOhOY5Q557/6/UoyOSXw==, tableContent=null), ArticleFig(id=1241057224110437110, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, language=EN, label=Fig.2, caption=Diffuse nitrogen losses from paddy fields during rice season and the reduction rate under different field ponding water level optimizations, figureFileSmall=UWxtjvWorGVKEIsr9dxgng==, figureFileBig=SJbeU2rrPQsN07Njj2JoIA==, tableContent=null), ArticleFig(id=1241057225645552393, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, language=CN, label=图2, caption=田面水位优化下水稻季氮素流失及相应的削减率

F0:现状情景;F1:优化水位情景1;F2:优化水位情景2;F3:优化水位情景3

, figureFileSmall=UWxtjvWorGVKEIsr9dxgng==, figureFileBig=SJbeU2rrPQsN07Njj2JoIA==, tableContent=null), ArticleFig(id=1241057225813324571, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, language=EN, label=Fig.3, caption=Reduction rates of watershed nitrogen losses under ditch optimization conditions, figureFileSmall=L47sJIvpBrkcmpeCcX06aA==, figureFileBig=Z+i+xLljylwAtIU6TxE3xg==, tableContent=null), ArticleFig(id=1241057225947542314, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, language=CN, label=图3, caption=沟渠优化下流域氮流失的削减率

D0:现状情景;D1:沟渠优化情景1;D2:沟渠优化情景2;ND:无沟渠情景

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P0:现状情景;P1:水塘优化情景1;P2:水塘优化情景2;P3:水塘优化情景3;NP:无水塘情景

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灰色数字(负值)为各环节总氮截留量;黑色加粗数字为各环节总氮流失量

, figureFileSmall=rZbwwImrhg0Tx1FLh9xoYw==, figureFileBig=LbsZ74tEaruVJHZVR0BbGA==, tableContent=null), ArticleFig(id=1241057226803180446, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, language=EN, label=Table 1, caption=

Main parameters setting for different scenarios

, figureFileSmall=null, figureFileBig=null, tableContent=
情景情景代码参数设置参数取值数据来源
田面水位情景F0现状情景排水水位(mm)0~80随生育期变动,各生育期参数设置见表2
F1优化水位情景0~120
F20~150
F30~180
沟渠情景D0现状情景曼宁系数0.1未维护沟渠[26]
D1沟渠优化情景0.24中等植被覆盖沟渠[25]
D20.35茂密植被覆盖沟渠[27]
ND无沟渠情景/无沟渠
水塘情景P0现状情景0.22~0.52当前现状
P10.37~0.67当前现状+15%
P2水塘优化情景水塘汇流面积比0.53~0.82当前现状+30%
P30.73~1.00当前现状+50%
NP无水塘情景0无水塘
田-沟-塘系统情景BL现状情景F0+D0+P0
OP最优情景F3+D2+P3
CK对照情景F0+ND+NP
), ArticleFig(id=1241057226924815278, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, language=CN, label=表1, caption=

不同情景的关键参数设置

, figureFileSmall=null, figureFileBig=null, tableContent=
情景情景代码参数设置参数取值数据来源
田面水位情景F0现状情景排水水位(mm)0~80随生育期变动,各生育期参数设置见表2
F1优化水位情景0~120
F20~150
F30~180
沟渠情景D0现状情景曼宁系数0.1未维护沟渠[26]
D1沟渠优化情景0.24中等植被覆盖沟渠[25]
D20.35茂密植被覆盖沟渠[27]
ND无沟渠情景/无沟渠
水塘情景P0现状情景0.22~0.52当前现状
P10.37~0.67当前现状+15%
P2水塘优化情景水塘汇流面积比0.53~0.82当前现状+30%
P30.73~1.00当前现状+50%
NP无水塘情景0无水塘
田-沟-塘系统情景BL现状情景F0+D0+P0
OP最优情景F3+D2+P3
CK对照情景F0+ND+NP
), ArticleFig(id=1241057227180667840, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, language=EN, label=Table 2, caption=

Water level setting at various rice growing stages for field water level scenarios(mm)

, figureFileSmall=null, figureFileBig=null, tableContent=
生育期灌溉水位适宜水位排水水位
F0F1F2F3
泡田期204080808080
返青期103050607080
分蘖前期204060708095
分蘖后期000000
拔节孕穗206080120150180
抽穗扬花206080100120150
灌浆期206080120150180
黄熟前期103060100140180
黄熟后期000000
), ArticleFig(id=1241057227373605848, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057216455832537, language=CN, label=表2, caption=

田面水位情景下不同生育期水位设置(mm)

, figureFileSmall=null, figureFileBig=null, tableContent=
生育期灌溉水位适宜水位排水水位
F0F1F2F3
泡田期204080808080
返青期103050607080
分蘖前期204060708095
分蘖后期000000
拔节孕穗206080120150180
抽穗扬花206080100120150
灌浆期206080120150180
黄熟前期103060100140180
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基于田-沟-塘系统优化的稻作流域氮素面源污染减排潜力评估
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刘连华 1 , 欧阳威 2, * , 白艳 2 , 郝芳华 3
中国环境科学 | 环境生态 2025,45(5): 2693-2699
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中国环境科学 | 环境生态 2025, 45(5): 2693-2699
基于田-沟-塘系统优化的稻作流域氮素面源污染减排潜力评估
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刘连华1 , 欧阳威2, * , 白艳2, 郝芳华3
作者信息
  • 1.中国农业科学院农业环境与可持续发展研究所,北京 100081
  • 2.北京师范大学环境学院,北京 100875
  • 3.北京师范大学水科学研究院,北京 100875
  • 刘连华(1991-),女,山东临沂人,副研究员,博士,主要从事流域水环境过程与污染物迁移转化研究.发表论文18篇..

通讯作者:

* 责任作者,教授,
Evaluation on the reduction potential of diffuse nitrogen pollution in paddy field watersheds based on field-ditch-pond system optimization
Lian-hua LIU1 , Wei OUYANG2, * , Yan BAI2, Fang-hua HAO3
Affiliations
  • 1.Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • 2.School of Environment, Beijing Normal University, Beijing 100875, China
  • 3.College of Water Sciences, Beijing Normal University, Beijing 100875, China
出版时间: 2025-05-20
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为全面评估稻作流域田-沟-塘系统优化条件下氮素面源污染的减排潜力,利用流域水文模型对典型稻作流域开展田面水位、沟渠和水塘多环节的情景优化模拟.结果表明,不同环节优化对氮素面源污染流失的截留效果不同,且不同水文年的截留效果存在一定差异.在田面水位优化环节,提高排水水位后的稻田总氮流失量比常规水位管理可减少7.9%~93.9%,枯水年的氮截留效果优于丰水年.在沟渠优化环节,提高沟渠植草密度后的流域氮流失削减率从0.8%提高到26.7%,丰水年的氮截留效果优于枯水年.在水塘优化环节,提高汇水面积后的流域氮流失削减率从10.5%提高到18.1%,枯水年的氮截留效果优于丰水年.在田-沟-塘系统多环节优化下,田面水位优化对流域氮流失的截留效果优于水塘优化和沟渠优化.稻作流域田-沟-塘系统多环节优化可以有效控制流域氮素面源污染流失,促进水稻生产的可持续发展.

稻作流域  /  面源污染  /  沟渠  /  水塘  /  氮削减

To comprehensively evaluate the reduction potential of diffuse nitrogen pollution under the field-ditch-pond system optimization, a watershed hydrological model was used to simulate the multi-scenario optimization of field ponding water level, ditch, and pond in a typical paddy field watershed. Results showed that different optimizations had different interception effects on diffuse nitrogen pollution, and that interception effects were different over distinct hydrological years. Under the optimization of field ponding water level, the total nitrogen loss from paddy fields after optimizing the drainage water level was reduced by 7.9% to 93.9% compared to conventional water level management, with the nitrogen interception effect being better in dry years than in wet years. Under ditch optimization, the reduction rate of nitrogen loss in the watershed increased from 0.8% to 26.7% after increasing the grass planting density of ditches, with the nitrogen interception effect being better in wet years than in dry years. Under pond optimization, the reduction rate of nitrogen loss in the watershed increased from 10.5% to 18.1% after increasing the catchment area of the pond, with the nitrogen interception effect being better in dry years than in wet years. Under the multi-optimization of the field-ditch-pond system, the interception effect of field ponding water level optimization on watershed nitrogen loss was better than that of pond optimization and ditch optimization. In summary, the multi-optimization of the field-ditch-pond system can effectively control the diffuse nitrogen pollution in paddy field watersheds and could promote the sustainable development of rice production.

paddy field watershed  /  diffuse pollution  /  ditch  /  pond  /  nitrogen reduction
刘连华, 欧阳威, 白艳, 郝芳华. 基于田-沟-塘系统优化的稻作流域氮素面源污染减排潜力评估. 中国环境科学, 2025 , 45 (5) : 2693 -2699 .
Lian-hua LIU, Wei OUYANG, Yan BAI, Fang-hua HAO. Evaluation on the reduction potential of diffuse nitrogen pollution in paddy field watersheds based on field-ditch-pond system optimization[J]. China Environmental Science, 2025 , 45 (5) : 2693 -2699 .
我国水稻产量和种植面积分别占全球的32%和19%,消耗了全国65%的农业用水和20%~25%的化肥[1-3].过量水肥投入导致稻田水肥利用率低、面源污染流失严重,引发了流域水体富营养化等一系列问题[4-5].稻田氮素径流流失已成为我国农业面源污染重要来源之一[6],特别是南方稻区降雨和施肥时期叠加,使面源污染流失严重[7].南方稻作流域稻田周围分布着沟渠和水塘,形成了田-沟-塘系统这种农业生态景观[8].随着对氮素面源污染防控的深入理解,从源头控制、过程消减到末端净化的多环节减排措施逐渐受到重视[9-10].充分发挥稻作流域田-沟-塘系统的作用,从稻田、沟渠和水塘多个环节进行优化管理,对流域氮素面源污染防控具有重要义.
针对稻作流域田-沟-塘系统,国内外学者开展了多环节优化的面源污染减排潜力研究[11-12].研究多集中于稻田控制灌溉-明沟控水-水塘湿地组合对水肥利用率和氮磷流失负荷的影响[13-14]、稻田施肥优化-植草沟渠-好氧塘组合对水质及植物生长的影响[15].对于稻田排水水位-沟渠植草密度-水塘汇水面积的多环节优化下稻作流域面源污染流失的系统研究较为缺乏.且目前多环节优化研究多集中于田间或区域尺度的点位监测.在不同水文、农田管理等条件下,所获得的污染截留效果差异较大,这对合理评估稻作流域面源污染减排潜力提出了挑战.
田间试验或区域监测是在特定观测尺度开展研究,难以反映长时间流域水文和元素循环特征,因此流域模型被应用于农业面源污染负荷模拟[16].其中,分布式水文模型SWAT被广泛用于评估农业流域面源污染流失以及预测不同管理措施对水环境的影响[17-18].针对稻作流域的模拟,学者对SWAT模型中稻田算法进行优化改良,增设稻田灌排管理水位设置,模拟稻田实际的水文循环过程,模拟稻田水位优化下的灌溉效率和节水潜力[19-22].利用SWAT模型中植草水道和坑塘模块可以模拟沟塘系统对氮磷流失的截留效果[23-25].值得注意的是,田面水位、沟渠和水塘优化对面源污染流失的截留效果与水文条件,特别是降雨条件密切相关.然而,目前针对不同水文条件下,流域尺度田-沟-塘系统多环节优化下氮素面源污染流失减排效果的研究相对薄弱.
基于以上背景,本文利用改进的SWAT模型开展流域面源污染模拟,探究不同水文条件下田面水位、沟渠和水塘优化下氮素面源污染流失特征,评估田-沟-塘系统多环节优化对氮素流失的截留效果.研究结果可为稻作流域面源污染防控提供科学依据.
选择位于长江流域稻作区的洑水流域(113°39′~113°47′E,31°19′~31°30′N)开展模型模拟.流域总面积121.4km2,河道总长52.5km.流域属于亚热带季风气候,多年平均气温16.6℃,平均降雨量1068mm.流域土地利用类型包括稻田、旱地、林地、水域和建筑用地.流域内稻田周围分布着自然沟渠和水塘,水域面积占流域总面积的7.9%(图1).
水稻种植模式为单季稻,5月下旬泡田整地,基肥施用后插秧,在分蘖期及孕穗期追施氮肥(3次氮肥施用比例为4:3:3),9月中下旬收获.除了分蘖后期和收获前晒田外,其他时期田面保持约20~50mm左右的水层.其他管理措施同常规农民操作.
为更好的模拟稻作流域水文过程,采用Ouyang等[21]根据稻田水文循环及污染物流失特点改进的SWAT模型进行模型建立.原模型中壶穴模块的构型设定、蒸散发过程、产汇流过程、侵蚀过程的部分代码被改良,增设能反映稻田灌排管理的水位控制模块.稻田灌排操作是以日尺度水位控制为基础,设置3条水位线:灌溉水位,当低于此水位线时触发灌溉操作;适宜水位,当达到此水位停止灌溉操作;排水水位,当超过此水位线时将触发排水过程.通过水位线设置,可以模拟实际灌溉、持水及排水过程.本研究模型中三条水位线的设置是基于长江流域典型单季稻的田间水位控制实验的结果[3].
模型构建所需数字高程模型采用地理空间数据云30m分辨率的DEM;土壤类型数据来源于中国科学院南京土壤所1:1000000土壤类型数据;土地利用分布数据经人工解译获得;土壤属性数据来自中国科学院南京土壤研究所的中国土壤数据库;气象数据从当地气象站获得;流域管理数据调研获得.
利用稻田土壤水含量监测数据及流域出口水质监测数据对模型进行率定验证.稻田土壤水的率定验证结果表明,改进的模型能够准确的模拟稻田长期淹水条件下土壤水趋于饱和的特征[3].流域出口的总氮和硝态氮的率定期和验证期的R2均在0.6以上,Ens均在0.5以上,这说明改进的SWAT模型能较好的模拟稻作流域的水文和氮素污染流失特征.
针对稻作流域田-沟-塘系统的特征,设置单环节情景(田面水位情景,沟渠情景,水塘情景)和田-沟-塘系统情景.单环节情景包括:4种田面水位情景(F0、F1、F2、F3)、4种沟渠情景(D0、D1、D2、ND)、5种水塘情景(P0、P1、P2、P3、NP).田-沟-塘系统情景包括:现状情景BL、最优情景OP、对照情景CK.每种情景的关键参数设置见表1表2.
水文条件对稻作流域氮素面源污染流失具有重要影响.因此,根据水稻生长季降雨特征,将近56年来研究期(1964~2019)化分为丰水年、平水年和枯水年3种情景.丰、平和枯水年,水稻季平均降雨量分别为905.7、574.2和331.9mm,且不同水文年降雨量之间存在显著差异(P<0.05).分别以F0、ND、NP、CK情景为对照,对各优化情景的氮流失削减率进行计算,以评估田-沟-塘系统优化对氮素流失的截留效率.
与现状情景(F0)相比,提高稻田排水水位可以有效降低氮流失量,随着排水水位的提高,氮流失削减率增加;而且不同水文年条件下,氮流失削减效果不同(图2).具体表现为,枯水年条件下,提高排水水位的削减率大于丰水年(P<0.05).丰水年总氮削减率为7.9%~53.0%,枯水年削减率为24.5%~93.9%.此外,提高排水水位对不同形态氮的削减率相差不大,总氮、有机态氮和无机态氮削减率分别为7.9%~93.9%、6.0%~94.9%和17.3%~92.0%.
不同沟渠优化情景下流域出口氮流失负荷削减率如图3所示.随着植草密度的增大,沟渠对流域氮流失负荷的削减率逐渐增强,并且有机态氮为沟渠截留的主要形式.D0情景下,沟渠对总氮、有机态氮和无机态氮流失的削减率分别为0.8%、1.0%和0.2%;D1情景下,削减率分别增加到12.9%、15.6%和3.6%;D2情景下,削减率分别增加到26.7%、33.1%和6.6%.不同水文条件下沟渠对氮的削减效果不同,表现为丰水年的效果大于枯水年(P<0.05).D2情景下,在丰水年,沟渠对总氮、有机态氮和无机态氮流失的削减率分别为42.6%、42.1%和14.2%;在枯水年,相应的削减率降低为14.5%、22.8%和1.9%.
不同田面水位情景下,植草沟渠对氮流失负荷的削减率不同,随着田面排水水位的提高,植草沟渠的截留效果降低.D1情景下,当田面水位为F0情景时,植草沟渠对总氮、有机态氮和无机态氮流失的削减率分别为12.9%、15.8%和3.6%;而当田面水位为F3情景时,相应的削减率分别降低为5.8%、7.2%和1.5%.D2情景下,当田面水位为F0情景时,植草沟渠对总氮、有机态氮和无机态氮流失的削减率分别为26.7%、33.1%和6.8%;而当田面水位为F3情景时,相应的削减率分别降低为10.9%、13.5%和2.6%.
不同水塘优化情景下流域出口氮流失负荷削减率如图4所示.随着水塘汇流面积的增加,流域出口氮流失负荷的削减率逐渐增强,并且有机态氮为水塘截留的主要形式.与NP情景相比,P0情景下水塘对总氮、有机态氮和无机态氮流失的削减率分别为10.5%、9.5%和8.5%.汇流面积增加时,水塘对总氮、有机态氮和无机态氮流失的削减率分别提高到13.1%~18.1%、12.4%~18.1%和9.9%~12.6%.不同水文年下水塘对氮的削减率不同,表现为枯水年的效果大于丰水年(P<0.05),这与沟渠对氮削减效果的趋势相反.P3情景下,在枯水年,水塘对总氮、有机态氮和无机态氮流失的削减率分别为26.2%、23.7%和25.2%;而在丰水年,相应的削减率分别降低为18.8%、21.8%和4.9%.
不同田面水位情景下,水塘对氮流失负荷的削减率不同,表现为随着田面排水水位的提高,水塘对氮流失的截留效果降低,这与沟渠对氮削减效果的趋势一致.P1情景下,田面水位为F0情景时,水塘对总氮、有机态氮和无机态氮流失的削减率分别为13.1%、12.4%和9.9%;田面水位为F3情景时,削减率分别降低为10.5%、8.4%和10.5%.同样地,P3情景下,当田面水位为F0情景时,水塘对总氮、有机态氮和无机态氮流失的削减率分别为18.1%、18.2%和12.6%;而当田面水位为F3情景时,相应的削减率分别降低为13.9%、11.8%和11.4%.
为深入理解田-沟-塘系统多环节优化对流域氮流失的影响,分析了BL和OP情景下流域氮流失削减率(图5).与无沟渠和水塘系统的对照情景(CK)相比,现状情景(BL)下流域总氮、有机态氮和无机态氮流失的削减率分别为11.2%、10.7%和8.7%;田-沟-塘系统多环节优化后(OP情景)相应的削减率分别提高到50.4%、58.2%和14.3%.
多环节最优情景下,流域氮流失截留效果表现为田面水位优化>水塘优化>沟渠优化(图6).具体截留效果表现为:流域陆面年均氮流失量为207.6t/a,其中51.0%氮流失来自稻田.在田面水位优化、沟渠优化和水塘优化环节,流域总氮流失量分别减少79.3、11.5和13.8t/a,最终103.0t/a总氮汇入附近水体.
在田面水位优化环节,提高稻田排水水位可以提高稻田水容量,从而减少径流发生量和氮磷流失量[28].与常规田面水位管理相比,将排水水位提高到最优高度(F3情景),稻田总氮流失量减少7.9%以上,最高可减少93.9%.田面水位优化在枯水年的阻控效果优于丰水年.这是因为枯水年降雨频率和降雨量较低,径流发生频率和径流量较低,特别是在特干旱年份没有降雨径流,因此在枯水年提高排水水位可有效降低或消除氮素径流流失;而丰水年降雨量大和降雨频率高,使田面水位处于较高水平,稻田水容量较低,即便提高排水水位,丰水年氮流失量仍较大.因此田面水位优化在丰水年的氮截留效果远低于枯水年.另外,有机态氮主要以土壤侵蚀的方式流失,无机态氮主要溶解于水中并随降雨径流流失[29-30].提高稻田排水水位,不但减少了径流量,而且减少了降雨造成的土壤侵蚀,因此各种形态的氮流失都能被有效截留.
在沟渠优化环节,提高植草密度可有效提高沟渠对面源污染流失的削减率[31].本研究结果表明,植草密度提高后,沟渠对流域氮流失的削减率从0.8%提高到26.7%.在水塘优化环节,提高汇水面积后,水塘对氮流失的削减率从10.5%提高到18.1%.以上结果表明如果维护改善好流域内沟塘系统,面源污染将会得到有效控制[28,32].随着田面排水水位的提高,沟塘系统对氮磷的截留效果降低.这是因为,沟塘系统对氮的截留效果与农田排水中氮浓度和负荷有关.流入沟塘的浓度越大,流失负荷量越大,沟塘截留效果越高[33-34].提高排水水位可以减少稻田径流量和氮磷流失量,因此导致沟塘截留效果降低.有机态氮是沟塘截留的主要形式,这是因为沟塘能有效降低径流水中土壤颗粒的沉淀[26,35-37].不同水文年下,沟渠和水塘对氮流失的截留效果不同.沟渠截留效果随着氮流失量的增加而增加[38],因此在丰水年氮流失量较大的情况下,沟渠的截留效果高于枯水年.水塘的截留效果除了与氮流失负荷有关外,还与水力停留时间和水塘的水容量有关[35,39].枯水年降雨量和降雨频率较低,稻田排水汇入水塘后有更多的水力停留时间,并且水塘水容量较高,水塘水外排频率和外排量较低;而丰水年降雨量较多,水塘即要容纳稻田排水又要容纳自然降雨,使水塘水容量较小,水力停留时间变短,水塘水外排频率增加.因此,在丰水年,水塘对氮流失的截留效果低于枯水年.
本研究稻田田面水位优化情景中排水水位的设置,是根据田间试验得出的不影响水稻正常生长的水位.因此,田-沟-塘系统优化可以在保证水稻产量的同时,显著提高稻田水容量,并有效减少流域氮磷流失负荷.在田面水优化环节,提高排水水位可以有效截留降雨,减少稻田水外排,减少稻田氮流失[14,28].通过提高稻田排水水位,截留的降雨和氮元素被储存在田面水中用于水稻吸收,从而降低灌溉需水量,提高肥料利用率.在沟渠阻控和水塘净化环节,沟渠和水塘能够有效截留稻田排水中的氮元素,且蓄积在沟塘系统中的水分和养分可通过循环灌溉被重新利用[40].综上所述,充分利用田-沟-塘系统,建立基于源头减排(提高稻田排水水位)、过程阻控(提高沟渠植草密度)和末端净化(提高水塘汇水面积)相结合的多环节面源污染流失控制技术,可有效提高稻作流域水资源利用率,降低流域面源污染流失,促进水稻生产的可持续发展.在我国南方稻作流域,稻田周边常常分布着沟渠和水塘,可以对原有土质沟渠或破损需要重建的水泥排水沟渠进行改造和升级,种植挺水植物和沉水植物,连通稻田内部沟塘,让更多的稻田排水先经过沟塘系统截留净化后,再排入河流或湖泊.值得注意的是,要加强沟塘的日常维护,定期对沟塘内植被进行养护管理或刈割,及时进行清淤处理,避免造成二次污染.此外,应注意在丰水年,田面水位控制时间不宜过长,避免水稻受淹造成减产;暴雨天气导致水塘蓄水量过大时,需及时排洪,降低溢塘的风险.
本研究利用改进的SWAT模型模拟了典型稻作流域田-沟-塘系统不同环节优化下氮素面源污染流失的减排潜力.由于模型结构、模型输入数据以及农业措施参数等设置的概化性,可能导致模拟结果存在一定的不确定性.此外,通过田间试验及文献调研获得的田面水位、沟渠和水塘相关参数的数值可能并不能完全代表流域内全部管理现状,由此造成的模拟误差在所难免.针对以上不确定性,本研究利用稻田土壤水含量及流域出口水质监测数据,不断调整模型参数以达到模拟值与实测值的近似.最终,模型率定期和验证期模拟均满足评价标准,表明模型在稻作流域具备较好的适用性.在今后研究中,可细化流域空间参数设置的准确性和差异性,进一步提高模型模拟的精度和准确度.
4.1 提高田面排水水位可以从源头有效降低稻田氮流失量.与常规水位管理相比,排水水位优化后,稻田总氮流失量可减少7.9%~93.9%.排水水位优化在枯水年的氮截留效果优于丰水年.
4.2 提高沟渠植草密度后,流域氮流失削减率从0.8%提高到26.7%.提高水塘汇水面积后,流域氮流失削减率从10.5%提高到18.1%.沟渠优化在丰水年的氮截留效果优于枯水年,而水塘优化在枯水年的氮截留效果优于丰水年.
4.3 田-沟-塘系统多环节优化下,流域氮流失截留效果表现为:田面水位优化>水塘优化>沟渠优化.最优情景下,田面水位优化、沟渠优化和水塘优化环节流域总氮流失量可分别减少79.3、11.5和13.8t/a.稻作流域田-沟-塘系统多环节优化可以有效降低流域面源污染流失,促进水稻生产的可持续发展.
  • 国家自然科学基金资助项目(U21A2039)
  • 中央级公益性科研院所基本科研业务费专项(BSRF202309)
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2025年第45卷第5期
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  • 接收时间:2024-09-06
  • 首发时间:2026-03-18
  • 出版时间:2025-05-20
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  • 收稿日期:2024-09-06
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国家自然科学基金资助项目(U21A2039)
中央级公益性科研院所基本科研业务费专项(BSRF202309)
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    1.中国农业科学院农业环境与可持续发展研究所,北京 100081
    2.北京师范大学环境学院,北京 100875
    3.北京师范大学水科学研究院,北京 100875

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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