Assessment Of Variablity In Glacier Melt And Snow Melt Runoff Under Projected Climatic Scenarios For A Data Scarce Himalayan River Basin

dc.contributor.guideProf. Aditi Bhadra and Prof. Arnab Bandhopadhyay
dc.coverage.spatial
dc.creator.researcherP. C. Vanlalnunchhani
dc.date.accessioned2024-09-25T10:12:51Z
dc.date.available2024-09-25T10:12:51Z
dc.date.awarded2024
dc.date.completed2024
dc.date.registered2019
dc.description.abstractThe snow and glacier melt along with rainfall induced runoff hold paramount newlineimportance in the hydrological regime of glaciated river basin. Comprehending the melt newlinedynamics and contribution of each runoff component is utmost important for evaluating newlineavailability and sustainability of water supply. Glacial and snow parameters are the newlineprimary inputs for estimation of melt runoff. Glaciers surface areas were obtained by newlineapplying Automatic Glacier Extraction Index (AGEI) in Landsat data in the glacierized newlineMago river basin, Arunachal Pradesh, eastern Himalaya. The glaciers count reduced newlinefrom 55 to 49 during the analysis period of 1988 2019, and the total area decreased newlinefrom 79.97 sq. km (1988) to 50.09 sq. km (2019), with a shrinkage rate of 0.96 sq. km newlineper annum. The glaciers Equilibrium Line Altitude (ELA) was determined for 15 newlineglaciers (size gt 1 sq. km) using Otsu thresholding technique on corrected NIR band. newlineThe temporal variations of ELA from 1988 2019 showed increasing trend with the newlineoverall rise of 137.3 m at the rate of 4.43 m per annum. Simulation of runoff and newlinegeneration of snow parameters were done in Spatially Distributed Snow and Glacier newlinemelt Runoff Model (SDSGRM). Analyses of snow parameters for snow months newline(November to April) from 2010 2019 showed an average snow density of 418.31 newlinekg m-3; snow depth of 1.81 m; SWE of 0.78 m; DDF of 0.49 cm °C-1 day-1; and newlinesnowmelt depth of 0.006, 0.015, 0.006 and 0.028 m using temperature index, radiation newlinetemperature index, advection driven index and energy balance method, respectively. newlineThe average modelling efficiency (ME) was observed to be 0.726 and 0.638 during newlinecalibration and validation periods, respectively. The average percentage contribution of newlinerunoff from all the methods was observed to be 82.42% from rain water yield (RWY), newline10.55% from snow water yield (SWY), and 7.03% from glacier water yield (GWY). newlineEmploying the bias corrected projected climate variables in SDSGRM, the future total newlinerunoff was projected to increase by 6.49 8.74%
dc.description.note
dc.format.accompanyingmaterialDVD
dc.format.dimensions
dc.format.extent
dc.identifier.urihttp://hdl.handle.net/10603/591638
dc.languageEnglish
dc.publisher.institutionDepartment of Agricultural Engineering
dc.publisher.placeItanagar
dc.publisher.universityNorth Eastern Regional Institute of Science and Technology (NERIST)
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Environmental
dc.titleAssessment Of Variablity In Glacier Melt And Snow Melt Runoff Under Projected Climatic Scenarios For A Data Scarce Himalayan River Basin
dc.title.alternative
dc.type.degreePh.D.

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