Page 22 - 《水资源与水工程学报》2025年第1期
P. 22

!36 "!1 #                         & ' ( ) & * + , -                               Vol.36No.1
               2025 $ 2 %               JournalofWaterResources&WaterEngineering                 Feb.,2025

            DOI:10.11705/j.issn.1672-643X.2025.01.03


               8_ ARIMA56P GMS fgš›Œ‚œ00ž


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                 BC<DE:TV213.4;P333   FGHIJ:A    FKLE:1672643X(2025)01001811

                         SimulationsofgroundwaterlevelsintheYangRiverBasin
                                   CombiningtheARIMAmethodwithGMS

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                              SUNFubao ,TONGJuxiu ,LIANGChang ,TONGJinwei
           (1.KeyLaboratoryofGroundwaterCirculationandEnvironmentalEvolution,MinistrayofEducation,ChinaUniversityofGeosciences(Beijing),
             Beijing100083,China;2.SchoolofWaterResourcesandEnvironment,ChinaUniversityofGeosciences(Beijing),Beijing100083,China)
                 Abstract:Conventionalgroundwaternumericalmodelsoftenfacelimitationsinpredictingfuturegroundw
                 aterlevelsduetothedifficultyofobtainingprecipitationandevaporationdata.Toaddressthisissue,this
                 studyputsforwardanimprovedgroundwaterlevelpredictionmethod.Weemploytheautoregressiveinte
                 gratedmovingaverage (ARIMA)modeltopredicttimeseriesdataforprecipitationandevaporation,then
                 integratethepredictionresultswiththegroundwaterflowmodelofgroundwatermodelingsystem(GMS)
                 tosimulatechangesingroundwaterlevelsintheYangRiverBasin.Thisnewmethodisthenappliedto
                 analyzethehistoricalmeteorologicaldataoftheYangRiverBasinfrom2000to2020.TheARIMAmodel
                 isusedtopredictprecipitationandevaporationin2021,andthepredicteddataareinputintotheGMSto
                 conductgroundwaterlevelsimulationexperiments.TheresultsindicatethattheGMSperformswellin
                 simulatinggroundwaterlevelsintheYangRiverBasin,withmostNSEvaluesrangingfrom0.71to0.96,
                 andRMSEvaluesbetween0.05and0.45m,demonstratinghighoverallaccuracy.TheARIMAmodel
                 exhibitsstrongpredictiveperformanceformeteorologicaldata ,withpredictionaccuracyforevaporation
                 outperformingthatforprecipitation.ThecombinedapproachoftheARIMAandGMSmodelsdemonstrates
                 highaccuracyandapplicability ,whichcanprovidetechnicalsupportforregionalgroundwaterresource
                 management.Theproposedmethodcanovercomethelimitationsofdependenceonfuturedataavailability
                 facedbyconventionalmodels,offeringaviablereferenceforgroundwaterlevelpredictioninsimilarre

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