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dc.contributor.authorAnand Verdhen
dc.contributor.authorBhagu R. Chahar
dc.contributor.authorAshwagosha Ganju
dc.contributor.authorOm P. Sharma
dc.date.accessioned2017-12-30T12:55:52Z
dc.date.available2017-12-30T12:55:52Z
dc.date.issued2016
dc.identifier.other%28ASCE%29HE.1943-5584.0001255.pdf
dc.identifier.urihttp://138.201.223.254:8080/yetl1/handle/yetl/4243532
dc.description.abstractSnow line altitude (SLA) defines the boundary of snow-free and snow-covered area. The efficiency of snow/ice-melt-runoff model and snowy/Himalayan watershed model depends on the estimation accuracy of the mean SLA for varying saturated snow cover (melting area) within seasonal and permanent SLA. Remotely sensed data are still in the phase of development to present quick and dependable input of SLA. This study is aimed to predict seasonal SLA, annual equilibrium line altitude (ELA), maximum annual SLA, melting zone, and their intraseasonal or/and interannual variations based on observed temperature in a watershed of the western Himalayas. The study area extends from 2,100 to 6,000 m altitudes (latitude: 32° 10′N to 32° 25′N; longitude: 77°E to 77° 40′E). Varying catchment participation (VCP) zonal altitude of melting and simulated relation naming applied basic oscillation (ABO) have been developed for SLA movement on weekly and monthly mean temperature data and simulation of monthly observed/estimated SLA, respectively. The VCP results suggested an upward shift of spring SLA by 700 m in March, whereas ABO results showed a 300-m upward shift of ELA during September in two decades from the 1980s. The VCP calibration parameters—temperature lapse rate of 0.554°C/100  m and saturated SLA mean air temperature of 5.75°C—have been designed to predict SLA using temperature and ablating snowpack at Solang (2,485 m altitude). The periodical shift in SLA has been verified with the snow cover disappearance data and combined impact of temperature and solar radiation at two stations. The VCP-computed SLA and ELA varied by ±5% with observed values, whereas the error in ABO-predicted monthly SLA including ELA was ±4%. Simplified VCP pattern variability, ABO trend of SLA, and SLA nomogram have been developed for the snowmelt hydrological models and other applications.
dc.publisherAmerican Society of Civil Engineers
dc.titleModeling Snow Line Altitudes in the Himalayan Watershed
dc.typeJournal Paper
dc.journal.volume21
dc.journal.issue1
dc.journal.titleJournal of Hydrologic Engineering
dc.identifier.doi10.1061/(ASCE)HE.1943-5584.0001255
dc.page04015056
dc.treeJournal of Hydrologic Engineering:;2016:;Volume ( 021 ):;issue: 001
dc.contenttypeFulltext


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