华北夏玉米农田氮淋失的定量预测 -pg电子娱乐平台

doi:10.12357/cjea.20230041华北地区夏玉米生产中农田氮淋失的定量预测[j].中国生态农业学报英文),2023,31(9):14391448zhaonitrogenleachinglossfromsummermaizeproduc-tionnorthchina[j].chinesejournaleco-agriculture,2023,31(9):14391448华北地区夏玉米生产中农田氮淋失的定量预测华北地区是我国冬小麦和夏玉米主产区,过去40多年间,随着大水漫灌和过量施肥等现象发生,该地区农田氮淋失呈现加重趋势,已经对地下水水质产生了严重影响。为探明华北地区面源污染的成因,进而提出相应阻控措施,本研究收集了1980—2021年国内外发表的华北地区夏玉米氮淋失研究文献,选取环境条件和农田管理措施作为自变量,基于线性模型、指数模型、多项式模型和多元回归模型等对氮淋失量进行模拟预测。结果表明,失与水分和肥料氮之间存在较大关联性,与土壤全氮、有机质含量和黏粒含量呈正相关关系,与秸秆还田、土层深度、土壤ph、砂粒含量呈现负相关关系。在单变量预测模型中,说明在华北地区夏玉米生产中应特别注重优化肥料用量。本研究所获得的多元逐步回归模型(y=23.07 1.14x有机质含量 0.34x黏粒含量0.13x砂粒含量 0.06x 0.18x水分渗漏量=0.414)优于指数模型、线性模型和多项式模型,具有较好的定量预测效果。考虑到水分渗漏测定过程复杂及方程的可应用性低,可以采用水分投入量替换水分渗漏量,但预测精度会受到影响。改善土壤物理条件(如质地)、秸秆还田和优化氮肥和灌溉,是今后华北地区夏玉米生产中降低氮淋失的关键措施。关键词:整合分析;水分渗漏量;回归模型;秸秆还田中图分类号:s153开放科学码(资源服务)标识码(osid):predictionnitrogenleachinglossfromsummermaizeproductionnorthchinazhaoxiaoying,wangnuoting,cuibin,yinshilei,yangxuan,mengfanqiaoenvironmentalsciences,chinaagriculturaluniversitybeijingkeylaboratoryprevention,controlfarmlandsoilpollution,beijing100193,china)abstract:northchinahasseenintensivefloodirrigationexcessivenitrogenfertilizationoverpastfourdecadesmaincerealcrop-producingregionleachingfromfarmlandregionhasrapidlyincreasedagriculturalintensification,non-pointsourcepollutionhasbecomeincreasinglyprominent.leachingduringcropproductionsystematically.literatureleachinglossfromsummermaizeproductionnorthchinapublishedfrom1980–2021soilpropertiesagriculturalmanagementpracticeswerechosenindependentvariablesleachinglossbasedlinear,exponential,polynomial,multipleregressionmodels.soilpropertiesincludedsoilorganicmatter,totalclaycontent,sandcontent,ph,agriculturalmanagementpracticesincludedstrawincorporation,soilwater.resultsshowedsoilwaterfertilizerinputsignificantlyinfluencedleachingloss.soilorganicmatter,soiltotalclaycontentpositivelycorrelatedleachingamount,whereasstrawincorporation,soildepth,ph,国家重点研发计划项目(2022yfd1900304)资助主要研究方向为面源污染与农业物质循环。e-mail:mengfq@cau.edu.cn主要研究方向为有机农业。e-mail:2986567083@qq.com收稿日期:2023-01-26　接受日期:2023-05-06nationalkeyresearchdevelopmentprojectchina(2022yfd1900304).correspondingauthor,e-mail:mengfq@cau.edu.cnreceivedjan.26,2023;acceptedmay2023中国生态农业学报(中英文)　2023chinesejournalofeco-agriculture,sep.2023,31(9):14391448http://www.ecoagri.ac.cnsandcontentnegativelycorrelatedleachingamount.single-factorsimulationmodel,exponentialequationmoreappropriatequantifyingtotalleachinglossinputthanlinearequation,indicatingoptimizingfertilizersummermaizeproductionnorthchina.alsoindicatedleachingfromsummermaizeproductionnorthchinarelativelyhighaftercertainthresholdfertilizationshouldimportantpractice.unlikemanypreviousstudiesdirectlyselectedfertilizerleachingloss,studycombinedwater(waterinput,waterbalance,waterpercolation)variouscombinationsoptimalprediction combination. waterpercolation had stepwiseregression equation leachingloss =23.07 1.14x soil organic matter 0.34x clay content 0.13x sand content 0.06x total 0.18xwater percolation betterthan predictioneffects exponential,linear, polynomialmodels. standardizedre- gression coefficients predictivevariables were 0.18, 0.11, 0.07, 0.23, soilorganic matter, clay content, sand con- tent, total waterpercolation, respectively, which showed waterpercolation mostimportant, followed soilorganic matter. considering waterpercolation calculation process, waterinput can replacewater percolation leachingloss =18.60 0.64x soil organic matter 10.27x straw incorporation 0.30x sand content 0.13x total 0.04xwater input predictionaccuracy regressionequation affected.future research leachingloss