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Analysisofbedmorphologicalfeatureparametersandmigration
velocitybasedonAIimagerecognition
1,2
1,2
1,2
1,2
ZHANGLingfeng ,LIUChunjing ,CAOWenhong ,JIANGXiaopeng ,ZHANGYu 1,2
(1.StateKeyLaboratoryofWatershedWaterCycleSimulationandRegulation,ChinaInstituteof
WaterResourcesandHydropowerResearch ,Beijing 100048,China;
2.KeyLaboratoryofSedimentScienceandNorthernRiverTraining.MinistryofWaterResources,ChinaInstituteof
WaterResourcesandHydropowerResearch,Beijing 100048,China)
Abstract:Thecharacteristicparametersandmigrationvelocityofbedformsarekeyfactorsinfluencinghydraulicre
sistanceandthemechanismofsedimenttransport ,whichareofsignificantimportanceforanalyzingriverbedevolu
tiontrends ,benthichabitatsystems,andtheimpactofhumanactivities.ThispaperutilizesAIVisionalFounda
tionModeltoobtainlong - duration ,highspatiotemporalresolutiondataonthedynamicdevelopmentofbedforms
fromthesidewallsofflume.Byadoptingimprovedmethodsforquantifyingbedformmorphologyandcalculatingmi
grationvelocity ,thebedform characteristicparametersandmigrationspeedsunderninedifferentconditionswere
extracted.Theresultsindicatethatunderdynamicequilibrium states ,significantrandom fluctuationsstillexistin
bedformcharacteristicparametersandmigrationvelocities ,withmigrationspeedshowinghighervolatilityandvaria
bility.Theaveragemigrationvelocityofthebedform increasesexponentiallywiththeintensificationofsediment
transportandbedloadmovement ,whilerelativewaveheightandsteepnessfollowaparabolicrelationshipwiththe
intensityofsedimentmovement.Approximately95% oftheleesidefaceanglesareconcentratedbetween10°and
30° ,showingalinearrelationshipwithsteepness.Bothbedform morphologyandmigrationvelocityexhibitapro
nouncedright - skeweddistributionwithtailingcharacteristics.Amongthem ,waveheightandwavelengthfitthe
Birnbaum - Saundersdistributionmostclosely,whileotherbedformmorphologycharacteristicsandmigrationveloci
tiesfollowaGammadistribution.
Keywords:bedform;AIimagerecognition;migrationvelocityofbedforms;intensityofbedloadmovement
(责任编辑:鲁 婧 韩 昆)
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