WOFOST模型对河南烤烟生长模拟的适用性评价

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关键词：WOFOST模型；河南烤烟；敏感性分析；适用性

中图分类号：S572 文献标识码：A

文章编号：0439-8114（2026）02-0107-06

DOI：10.14088/j.cnki.issn0439-8114.2026.02.016 开放科学（资源服务）标识码（OSID）：口

Applicability evaluation of WOFOST model for flue-cured tobacco growth simulation in Henan

WANGChen 1，2 ，LIWen-feng1，²，WANGWei-min1，2

（1.ChinaMetelicaldmstratioenaKeyboratoyofgroetelalupptdApldeego4a；2.XuchangMeteorological Bureau of Henan Province，Xuchang 461ooo，Henan，China）

Abstract：Inordertoclarifytheapplicabilityof theWOFOSTmodeltoHenanflue-curedtobacco，sensitviyanalysisofmodelparameterswasconductedbyOTAmethodbasedonfieldexperimentaldata，meteorologicaldataandagrometeorologicaloservationdatafrom2013to2O24.Thetrialanderormetodwasusedincombinationwithexperimentaldatatoadjustmodelparametersandevaluatetheaplicabilityof the modeltothegrowthanddevelopmentof Henan tobacco.TheresultsshowedthatSPAN，TSUM1， SLATB0.0，DTSMTB30，EEFTB40，TMPFTB20，AMAXTB0.0，CVL andRMS were identifiedas highlysensitive parameters throughensitivityanalysis.Using thedebuggedmodeltosimulateandverifythegrowthpriodandbiomassofluecuredtobaothe R2 values forthebud stage and mature stageof tobacco were 0.89 and0.83，RMSE were 3.4and2.4days，and NRMSE were 1.8% and 0.9% ，respectively. The RMSE of the model for simulating the leaf dry weight，stem dry weight，and leaf area index of tobacco were 2 198.0kg/hm2 ， 220.4kg/hm2 ，and 0.2m2/m2 ，and the NRMSE were 11.9% ， 17.4% ，and 11.8% ，respectively.The adjusted model perforedwellinsimulatingthegowthanddevelopmenprocessoftobaccleaves.Bycomparingthesimulatedyieldsdeterinedbyfour methods，itwasfoundthatcalculatingtheaverageofdailyleafdryweightdataforthefrst6Odaysofmaturitythroughthemodelhad thebest fitting effect as the simulated yield，with a simulation accuracy of 89.5% ，RMSE of 326.1kg/hm2 ，and NRMSE of 10.7% . The model，afterparameterdbuging，couldacuratelysiulatetehangesintegrowthprocsofHenantobacco，providingsientific management basis for actual production.

ey Words：WOFOST model; Henan flue-cured tobacco；sensitivity analysis；applicability

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