摘要关于森林可燃物含水率的研究一直是国际上的前沿和热点，影响森林可燃物含水率的因素有很多。本文为了研究不同时滞对可燃物含水率预测模型精度的影响，对2010年春季大兴安岭地区盘古林场樟子松(Pinussylvestrisvar.Mongolica）、兴安落叶松（Larixgmelinii）、白桦林(Betulaplatyphylla)、杨桦（Betulaplatyphylla）林分下可燃物含水率进行连续的观测，分析不同时滞对可燃物含水率预测模型精度的影响，为提高气象要素法的预测精度和更准确的预测森林火险提供科学依据。在四块样地里，每块样地按照1h、10h、100h不同时滞分为三组。运用SPSS软件对不同时滞对可燃物含水率的影响进行研究。结果表明：（1）在进行地表死可燃物含水率的预测时，应依据不同显著性气象因子作为建模预测时的变量；其中当日降水量和R、前1天降水量和Ra1以及前2天平均相对湿度Ha2是影响其含水率变化最重要的因子。（2）同一林型不同时滞，樟子松林、兴安落叶松林、白桦林中1时滞、10时滞、100时滞差异显著；杨桦林中1时滞与10时滞差异不显著、与100时滞差异显著。同一时滞不同林型，1时滞的樟子松与杨桦差异不显著、兴安落叶松与白桦差异不显著；10时滞的樟子松与兴安落叶松、白桦相互差异不显著、与杨桦差异显著；100时滞的各个林型均相互差异不显著。因此运用时滞对可燃物含水率进行预测的模型精度较高。关键词：大兴安岭可燃物含水率预测模型精度验证时滞AbstractResearchonthemoisturecontentofforestcombustibleshasalwaysbeenaninternationalfrontierandhotspot,andtherearemanyfactorsaffectingthemoisturecontentofforestcombustibles.Inordertostudytheinfluenceofdifferenttimedelaysontheaccuracyofthepredictionmodelofcombustiblemoisturecontent,Pinussylvestrisvar.Mongolica,LarixgmeliniiandBetulaplatyphyllaintheDaxing'anlingareainspring2010.Betulaplatyphyllastandsforcontinuousobservationofthemoisturecontentofcombustibles,andanalyzestheinfluenceofdifferenttimedelaysontheaccuracyofthepredictionmodelofcombustiblemoisturecontent,inordertoimprovethepredictionaccuracyofmeteorologicalelementsmethodandmoreaccuratelypredictforestfireinsuranceScientificbasis.Inthefourplots,eachplotwasdividedintothreegroupsaccordingtodifferenttimelagsof1h,10hand100h.SPSSsoftwarewasusedtostudytheeffectofdifferenttimelagsonthemoisturecontentofcombustibles.Theresultsshowthat:(1)Whenpredictingthemoisturecontentofsurfacedeadcombustibles,itshouldbebasedondifferentsignificantmeteorologicalfactorsasthevariablesinthemodelingprediction;thedailyprecipitationandR,thepreviousdayprecipitationandRa1andthefirst2ThedailyaveragerelativehumidityHa2isthemostimportantfactoraffectingthechangeofwatercontent.(2)Differenttimelagsofthesameforesttype,thedifferenceof1lag,10lagand100laginPinussylvestrisvar.mongolicaforest,Xing'anlarchforestandbirchforestwassignificant;thedifferencebetween1timelagand10laginYanghuaforestwasnotsignificant,and100Thetimelagissignificant.TherewasnosignificantdifferencebetweenPinussylvestrisvar.mongolicaandBetulaplatyphyllainthesametimedelay,andtherewasnosignificantdifferencebetweenPinussylvestrisvar.mongolicaandBetulaplatyphylla.ThedifferencebetweenPinussylvestrisvar.mongolicaandXing'anlarchandBetulaplatyphyllaat10lagswasnotsignificant.Thedifferenceinbirchwassignificant;theindividualforesttypeswith100lagswerenotsignificantlydifferentfromeachother.Therefore,themodelforpredictingthemoisturecontentofcombustibleswithtimelagishighlyaccurate.keywords:Daxinganlingregionfuelmoisturesamplingmethodsmodelaccuracytimelag目录1材料与方法............................................................11.1研究区概况...............................................
